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.

中文翻译：

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关于美国冠状病毒大流行与犯罪之间关系的初步证据

COVID-19大流行导致数以百万计的美国人的日常活动发生重大变化，许多企业和学校关闭，公共活动取消，各州推出了全屋服务订单。本文使用警察记录的公开犯罪数据来了解2020年前几个月在美国16个大城市中常见犯罪类型的发生率如何变化。以前的季节性自动回归综合移动平均（SARIMA）犯罪模型在没有大流行的情况下，使用几年时间来预测2020年预期的犯罪发生频率。然后将这些模型的预测与大流行初期几个月的实际犯罪频率进行比较。公众受到严重攻击的频率没有发生重大变化，或者（与政策制定者的关注相反），住宅受到严重攻击的频率没有任何变化。在某些城市，住宅盗窃案有所减少，但非住宅盗窃案变化不大。在某些城市，机动车盗窃有所减少，而机动车盗窃的方式却有所不同。这些结果可为日后研究冠状病毒大流行与不同犯罪之间的关系提供建议。