Disentangling community-level changes in crime trends during the COVID-19 pandemic in Chicago

Crime Science

Gian Maria Campedelli¹  Serena Favarin²  Alberto Aziani²  Alex R. Piquero³ 

[1] Department of Sociology and Social Research, University of Trento, Trento, Italy;School of Political and Social Sciences, Università Cattolica del Sacro Cuore, Milan, Italy;Transcrime-Joint Research Centre on Transnational Crime, Milan, Italy;University of Miami, Coral Gables, FL, USA;Monash University, Melbourne, Australia;

关键词: Coronavirus;    Structural Bayesian Time-Series;    Communities;    Sars-CoV-2;    Pandemic;    Crime trends;   

DOI  :  10.1186/s40163-020-00131-8

来源: Springer

【 摘 要 】

Recent studies exploiting city-level time series have shown that, around the world, several crimes declined after COVID-19 containment policies have been put in place. Using data at the community-level in Chicago, this work aims to advance our understanding on how public interventions affected criminal activities at a finer spatial scale. The analysis relies on a two-step methodology. First, it estimates the community-wise causal impact of social distancing and shelter-in-place policies adopted in Chicago via Structural Bayesian Time-Series across four crime categories (i.e., burglary, assault, narcotics-related offenses, and robbery). Once the models detected the direction, magnitude and significance of the trend changes, Firth’s Logistic Regression is used to investigate the factors associated to the statistically significant crime reduction found in the first step of the analyses. Statistical results first show that changes in crime trends differ across communities and crime types. This suggests that beyond the results of aggregate models lies a complex picture characterized by diverging patterns. Second, regression models provide mixed findings regarding the correlates associated with significant crime reduction: several relations have opposite directions across crimes with population being the only factor that is stably and positively associated with significant crime reduction.

【 授权许可】

CC BY