COVID-19 poses a dramatic challenge to health, community life, and the economy of communities across the world. While the properties of the virus are similar from place to place, the impact has been dramatically different from place to place, due to such factors as population density, mobility, age distribution, etc. Thus, optimum testing and social distancing strategies may also be different from place to place. The Epidemiology Workbench provides access to an agent-based model in which

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... phic, geographic, and public health information a community together with a social distancing and testing strategy may be input, and a range of possible outcomes computed, to inform local authorities on coping strategies. The model is adaptable to other infectious diseases, and to other strains of coronavirus. The tool is illustrated by scenarios for the cities of Urbana and Champaign, Illinois, the home of the University of Illinois at Urbana-Champaign. Our calculations suggest that massive testing is the most effective strategy to combat the likely increase in local cases due to mass ingress of a student population carrying a higher viral load than that currently present in the community.