The code allows you to model epidemic spread such as Covid-19. The current implementation can be run on New York, Pennsylvania states and for individual counties as well. The code can be easily adopted for any input country, state or any demographic region.
Developed by Joydeep Munshi and Indranil Roy at Lehigh University
J. Munshi, I. Roy, G. Balasubramanian, Spatiotemporal dynamics in demography-sensitive disease transmission: COVID-19 spread in NY as a case study. https://arxiv.org/ftp/arxiv/papers/2005/2005.01001.pdf
This program implements a version of Cellular Automata framework (CA) to investigate spatio-temporal dynamics of disease outbreak sensitive to demographic features such as population density, mobility and employment status. The code implement here uses Matlab's vectorization and mapping toolbox.
Different implementations may lead to slightly different behavour and/or results, but there is nothing wrong with it, as this is the nature of random walks and all metaheuristics.
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AutomataSpreadModel.m - This script contains all the required functions to run the spatio-temporal dynamics
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NYSpopulation.m - This script contains preprocessing data from NY state shape files using mapping toolbox. The function provides normalized population density data for each county and initial cell states inside a demography. Note: This script can be modiefied with appropriate shape files for different regions/demography.
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PASpopulation.m - This script contains preprocessing data from PA state shape files using mapping toolbox. The function provides normalized population density data for each county and initial cell states inside a demography.
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script.m - This script contains the sampling of AutomataSpreadModel script and outputs the end states for a given simulation time.