ABSTRACT
As a result of the changes in social behavior due to lockdown measures aimed to avoiding COVID-19 infection, changes in crime patterns have been observed in several cities around the world. This study has two objectives: (1) Analyze the spatio-temporal patterns of the incidence of street robbery and vehicle theft in Mexico City, before and after the social distancing measures begun. Throughout this period, it has been shown a decrease in high-impact robberies in Mexico City. However, changes in spatial patterns have not been studied yet. (2) Propose an algorithm for the visualization of spatio-temporal relationships of crimes to identify near repeat patterns. These two objectives are considered relevant to identify areas of repeat victimization, especially before an imminent return to routine activities in the city, such as the return to school, the reopening of restaurants, movie theaters, shopping malls and other businesses;and thus be able to contribute to identify and prevent these crimes. One of the main results is that despite crime volumes decreased, some specific crime locations remained after the lockdown. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.