Analysis and description of crimes in Mexico City using point pattern analysis within networks

Abstract

Mexico City has one of the largest urban areas in the world. Because of its large population and other social factors, it has a high incidence of crime, which was raising serious concerns in the inhabitants and the authorities as well. We analyse the spatial distribution of crime incidence in Mexico City between January 2018 and December 2019. The results focus the location of high-risk areas for different kind of crimes and permit to detect those streets where crime rate is higher than the average rate. In this study, we consider the data as a realization of spatial point processes. Our analysis shows the existence of clusters with high crime incidence running east-west across the central part of the urban area.