Abstract
Abstract
COVID-19 is not a universal killer. We study the spread of COVID-19 at the county level for the United States up until the 15th of August, 2020. We show that the prevalence of the disease and the death rate are correlated with the local socio-economic conditions often going beyond local population density distributions, especially in rural areas. We correlate the COVID-19 prevalence and death rate with data from the US Census Bureau and point out how the spreading patterns of the disease show asymmetries in urban and rural areas separately and are preferentially affecting the counties where a large fraction of the population is non-white. Our findings can be used for more targeted policy building and deployment of resources for future occurrence of a pandemic due to SARS-CoV-2. Our methodology, based on interpretable machine learning and game theory, can be extended to study the spread of other diseases.
Subject
Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Information Systems
Cited by
35 articles.
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