Hou Miaomiao, Zeng Zhaolong, Hu Xiaofeng, Hu Jinming
School of Information Technology and Cyber Security, People's Public Security University of China, Beijing 102628, China.
J Saf Sci Resil. 2022 Dec;3(4):340-352. doi: 10.1016/j.jnlssr.2021.10.008. Epub 2022 Feb 17.
The COVID-19 pandemic is strongly affecting many aspects of human life and society around the world. To investigate whether this pandemic also influences crime, the differences in crime incidents numbers before and during the pandemic in four large cities (namely Washington DC, Chicago, New York City and Los Angeles) are investigated. Moreover, the Granger causal relationships between crime incident numbers and new cases of COVID-19 are also examined. Based on that, new cases of COVID-19 with significant Granger causal correlations are used to improve the crime prediction performance. The results show that crime is generally impacted by the COVID-19 pandemic, but it varies in different cities and with different crime types. Most types of crimes have seen fewer incidents numbers during the pandemic than before. Several Granger causal correlations are found between the COVID-19 cases and crime incidents in these cities. More specifically, crime incidents numbers of theft in Washington DC, Chicago and New York City, fraud in Washington DC and Los Angeles, assault in Chicago and New York City, and robbery in Los Angeles and New York City, are significantly Granger caused by the new case of COVID-19. These results may be partially explained by the Routine Activity theory and Opportunity theory that people may prefer to stay at home to avoid being infected with COVID-19 during the pandemic, giving fewer chances for crimes. In addition, involving new cases of COVID-19 as a variable can slightly improve the performance of crime prediction in terms of some specific types of crime. This study is expected to obtain deeper insights into the relationships between the pandemic and crime in different cities, and to provide new attempts for crime prediction during the pandemic.
新冠疫情正在对全球人类生活和社会的诸多方面产生重大影响。为了调查这场疫情是否也会影响犯罪情况，我们研究了四个大城市（即华盛顿特区、芝加哥、纽约市和洛杉矶）在疫情之前和期间犯罪事件数量的差异。此外，还检验了犯罪事件数量与新冠新增病例之间的格兰杰因果关系。在此基础上，利用具有显著格兰杰因果相关性的新冠新增病例来提高犯罪预测性能。结果表明，犯罪总体上受到新冠疫情的影响，但在不同城市和不同犯罪类型中情况有所不同。大多数犯罪类型在疫情期间的事件数量比之前有所减少。在这些城市的新冠病例与犯罪事件之间发现了若干格兰杰因果关系。更具体地说，华盛顿特区、芝加哥和纽约市的盗窃犯罪事件数量、华盛顿特区和洛杉矶的欺诈犯罪事件数量、芝加哥和纽约市的袭击犯罪事件数量，以及洛杉矶和纽约市的抢劫犯罪事件数量，均受到新冠新增病例的显著格兰杰因果影响。这些结果可能部分由日常活动理论和机会理论来解释，即在疫情期间人们可能更愿意待在家里以避免感染新冠，从而减少了犯罪机会。此外，将新冠新增病例作为一个变量纳入，在某些特定类型的犯罪预测方面可以略微提高预测性能。本研究有望更深入地了解不同城市中疫情与犯罪之间的关系，并为疫情期间的犯罪预测提供新的尝试。
