Abstract
The COVID-19 pandemic led to substantial changes in the daily activities of millions of Americans, with many businesses and schools closed, public events cancelled and states introducing stay-at-home orders. This article used police-recorded open crime data to understand how the frequency of common types of crime changed in 16 large cities across the United States in the early months of 2020. Seasonal auto-regressive integrated moving average (SARIMA) models of crime in previous years were used to forecast the expected frequency of crime in 2020 in the absence of the pandemic. The forecasts from these models were then compared to the actual frequency of crime during the early months of the pandemic. There were no significant changes in the frequency of serious assaults in public or (contrary to the concerns of policy makers) any change to the frequency of serious assaults in residences. In some cities, there were reductions in residential burglary but little change in non-residential burglary. Thefts of motor vehicles decreased in some cities while there were diverging patterns of thefts from motor vehicles. These results are used to make suggestions for future research into the relationships between the coronavirus pandemic and different crimes.
Highlights
The current coronavirus pandemic is drastically altering many aspects of life around the world
To increase the robustness of the results, this study focused on crime types which are known to be both relatively likely to be reported to police and relatively unaffected by variations in police recording practices
Shown on each figure are the date of the first COVID-19 case in the United States, together with the dates on which the relevant city or state government closed schools and issued a stay-athome order
Summary
The current coronavirus pandemic is drastically altering many aspects of life around the world. To better estimate the expected frequency of crime in the absence of the pandemic, this report uses seasonal auto-regressive integrated moving average (SARIMA) models of the frequency of different crime types in each city between 1 January 20162 and the first confirmed case of COVID-19 in the United States on 20 January 2020 (Holshue et al 2020). The models incorporate both a dummy trend variable and 51 dummy variables for weekly seasonal terms, along with a variable denoting whether the week included a US federal public holiday. The online supplementary material for this article includes a summary of the data made available (Additional file 1) and the co-efficients for each SARIMA model (Additional file 2)
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