Disentangling the Impact of Covid-19: An Interrupted Time Series Analysis of Crime in New York City

Stephen Koppel, Joel A. Capellan, Jon Sharp

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


The Covid-19 stay-at-home restrictions put in place in New York City were followed by an abrupt shift in movement away from public spaces and into the home. This study used interrupted time series analysis to estimate the impact of these changes by crime type and location (public space vs. residential setting), while adjusting for underlying trends, seasonality, temperature, population, and possible confounding from the subsequent protests against police brutality in response to the police-involved the killing of George Floyd. Consistent with routine activity theory, we found that the SAH restrictions were associated with decreases in residential burglary, felony assault, grand larceny, rape, and robbery; increases in non-residential burglary and residential grand larceny motor vehicle; and no change in murder and shooting incidents. We also found that the protests were associated with increases in several crime types: felony assault, grand larceny, robbery, and shooting incidents. Future research on Covid-19’s impact on crime will need to account for these potentially confounding events.

Original languageEnglish (US)
JournalAmerican Journal of Criminal Justice
StateAccepted/In press - 2022

All Science Journal Classification (ASJC) codes

  • Law


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