 Exploiting public data on crime in Los Angeles, and relying on routine activity and pattern theories of crime, this work investigates whether and how new coronavirus containment policies have an impact on crime trends in a metropolis using Bayesian structural time-series (BSTS) models. The article specifically focuses on nine urban crime categories , daily monitored from January 1st 2017 to March 28th 2020.
<clarity>  Exploiting public data on crime in Los Angeles, and relying on routine activity and pattern theories of crime, this work investigates whether and how new coronavirus containment policies have an impact on crime trends in a metropolis using Bayesian structural time-series (BSTS) models. The article specifically focuses on nine urban crime categories , daily monitored from January 1st 2017 to March 28th 2020.
 Exploiting public data on crime in Los Angeles, and relying on routine activity and pattern theories of crime, this work investigates whether and how new coronavirus containment policies have an impact on crime trends in a metropolis using Bayesian structural time-series and focuses on nine urban crime categories , daily monitored from January 1st 2017 to March 28th 2020.