Background: Across 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.
Objective: To determine the effect of social distancing measures in unique regions.
Design: An agent-based simulation model.
Setting: Agent-based model applied to Dane County, Wisconsin; the Milwaukee metropolitan (metro) area; and New York City (NYC).
Patients: Synthetic population at different ages.
Intervention: Different times for implementing and easing social distancing measures at different levels of adherence.
Measurements: The 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.
Results: The 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.
Limitation: The effect of weather conditions on transmission dynamics was not considered.
Conclusion: The timing of implementing and easing social distancing measures has major effects on the number of COVID-19 cases.
Primary funding source: National Institute of Allergy and Infectious Diseases.