Social distancing to slow the U.S. COVID-19 epidemic: an interrupted time-series analysis

Mark J Siedner; Guy Harling; Zahra Reynolds; Rebecca F Gilbert; Atheendar Venkataramani; Alexander C Tsai

Our findings should be interpreted with the following limitations in mind. Our estimates would be biased toward the null if: 1) state and local governments had intensified social distancing measures in response to a worsening epidemic, 2) there were significant violations of the stable unit treatment value assumption (e.g., workplace closures of large employers that had spillover effects across state lines), or 3) surveillance and testing intensified during the study period (thereby resulting in increased case reporting). Moreover, statewide restrictions on internal movement were often implemented after other social distancing measures had already been applied, further biasing our estimate toward the null. Our study was also limited by little observation time after statewide restrictions on internal movement were implemented. Finally, our estimated effects of social distancing in terms of mean daily case growth rates cannot be extrapolated linearly beyond the study period, nor can they answer questions about the appropriate timing of rescinding such measures.