• Oguzhan Alagoz, Ajay K Sethi, Brian W Patterson, Matthew Churpek, and Nasia Safdar.
• University of Wisconsin-Madison, Madison, Wisconsin (O.A., A.K.S.).
• Ann. Intern. Med. 2021 Jan 1; 174 (1): 505750-57.

BackgroundAcross the United States, various social distancing measures were implemented to control the spread of coronavirus disease 2019 (COVID-19). However, the effectiveness of such measures for specific regions with varying population demographic characteristics and different levels of adherence to social distancing is uncertain.ObjectiveTo determine the effect of social distancing measures in unique regions.DesignAn agent-based simulation model.SettingAgent-based model applied to Dane County, Wisconsin; the Milwaukee metropolitan (metro) area; and New York City (NYC).PatientsSynthetic population at different ages.InterventionDifferent times for implementing and easing social distancing measures at different levels of adherence.MeasurementsThe model represented the social network and interactions among persons in a region, considering population demographic characteristics, limited testing availability, "imported" infections, asymptomatic disease transmission, and age-specific adherence to social distancing measures. The primary outcome was the total number of confirmed COVID-19 cases.ResultsThe timing of and adherence to social distancing had a major effect on COVID-19 occurrence. In NYC, implementing social distancing measures 1 week earlier would have reduced the total number of confirmed cases from 203 261 to 41 366 as of 31 May 2020, whereas a 1-week delay could have increased the number of confirmed cases to 1 407 600. A delay in implementation had a differential effect on the number of cases in the Milwaukee metro area versus Dane County, indicating that the effect of social distancing measures varies even within the same state.LimitationThe effect of weather conditions on transmission dynamics was not considered.ConclusionThe timing of implementing and easing social distancing measures has major effects on the number of COVID-19 cases.Primary Funding SourceNational Institute of Allergy and Infectious Diseases.

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