COVID-19 — Worldwide/Unknown
Abstract
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The COVID-19 pandemic dramatically changed human mobility patterns, necessitating epidemiological models which capture the effects of changes in mobility on virus spread1. We introduce a metapopulation SEIR [susceptible-exposure-infective-recovered] model that integrates fine-grained, dynamic mobility networks to simulate the spread of SARS-CoV-2 in 10 of the largest US metropolitan statistical areas. Derived from cell phone data, our mobility networks map the hourly
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