Weekly Crime Concentration

Objectives Examine and visualise the temporal concentration of different crime types and detect if their intensity varies through distinct moments of the week. Methods The “heartbeat of the crime signal” is constructed by overlapping the weekly time they were suffered. This study is based on more than 220,000 crimes reported to the Mexico City Police Department between January 2016 and March 2020 to capture the day and time of crimes and detect moments of the week in which the intensity exceeds the average frequency. A new metric for the temporal concentration of crime is constructed for different types of crime and regions of the city based on the corresponding heartbeats. Results The temporal concentration of crime is a stable signature of different types of crime. The intensity of robberies and theft is more homogeneous from Monday to Sunday, but robberies of a bank user are highly concentrated in a week, meaning that few hours of the week capture most of the burning moments. The concentration is not homogeneously distributed in the city, with some regions experiencing a much higher temporal concentration of crime. Conclusions Crime is highly concentrated when observed in its weekly patterns, but different types of crime and regions exhibit substantially distinct concentration levels. The temporal trace indicates specific moments for the burning times of different types of crime, which is a critical element of a policing strategy.

The Spatial Concentration and Dispersion of Homicide during a Period of Homicide Increase in Brazil

This study applies the principles of measuring micro-place crime concentration and the spatial dispersion of crime increase to the geographic unit of cities in Brazil. We identify that a small number of cities account for a large cumulative proportion of homicides, and that during a period of homicide increase 30 cities out of 5570 accounted for the equivalent national increase in homicides. The majority of the 30 cities were not established high homicide cities but instead were new emerging centers of homicide that neighbor high homicide cities. We suggest the findings can be used to better target effective programs for decreasing homicides.

Spatial Analysis of Crime in Socially Distressed Cluster in Oke Ogun Region, Oyo State, Nigeria

The study is a methodological approach to measuring crime in distressed cluster in different geographic resolutions in Oke-Ogun Region of Oyo State with a view to examining spatial variation in crime concentration in the area. Crime reports of Oke-Ogun Region were collated from the Nigeria Police records on eighteen typologies of crime categorised in police blotter into crime against person and property from 2005 to 2015. Analytical techniques adapted to examine crime concentration were Zscore and Location Quotient of Crime (LQC). For the purpose of having the real picture of crime concentration as one moves across different spatial scales of settlements, settlements in the area were spatially disaggregated into three levels; urban, semi urban and rural settlements. Analysis with the use of Z-score showed that store breaking and arson for crime against property and murder for crime against person were more concentrated in rural settlements than every other crime type relatively. House breaking for crime against property, and breach of peace for crime against person were more concentrated in semi urban settlements, while burglary for crime against property, rape and indecent assault and unnatural offence for crime against person were conspicuously concentrated in urban settlements. Concentration of property crime therefore decreases as one move from rural areas to urban areas with Z scores of -1.15, 0.33 and 1.84 in urban, semi urban and rural areas respectively. However, the concentration of crime against person increases as one move from rural areas through semi urban to urban settlement, with Z scores of 4.06, 0.56 and -3.72 in urban, semi urban and rural areas respectively. Further analysis with LQC was done, and it was observed that rural settlements had (LQC =0.98) a disproportionately low share of 2% of crimes against person relative to urban settlement and that armed robbery, arson and false pretense / cheating are endemic nature of both semi urban and rural settlements. The study concluded that the cluster of aggregated crime types conformed to regular spatial pattern with declining crime cluster as one move from urban areas through semi urban to rural settlement.

Crime against Businesses: Temporal Stability of Hot Spots in Mexicali, Mexico

In developing countries, crime is a serious problem that affects the operation and viability of firms. Offenses such as vandalism, robbery, and theft raise the operating costs of firms and imposes on them indirect costs. The literature on spatial analysis of crime is vast; however, relatively little research has addressed business crime, especially in developing countries’ cities. Spatial and temporal analysis of crime concentration represents a basic input for the design and implementation of appropriate prevention and control strategies. This article explores the spatial concentration and stability of thefts committed against commercial establishments in the city of Mexicali, Mexico, from 2009 to 2011 using the Gini coefficient, Lorenz curve, and decile maps. Results revealed that thefts were highly concentrated in a small percentage of urban basic geostatistical areas. Moreover, a portion of these areas were classified as having the highest deciles of thefts (hot spots) and remained in this group throughout the period. In both cases, the relationship between crime and place was close to the 80/20 rule, or the Pareto principle.

How Concentrated are Police on Crime? A Spatiotemporal Analysis of the Concentration of Police Presence and Crime

Purpose Police patrol has undergone an evidence-based and data driven transition in the beginning of the 21st century. While crime patterns are well researched, patterns of police presence are not. Despite the abundance of available GPS data, little is known about the spatiotemporal patterns of police forces. Given the paucity of evidence on where everyday policing takes place, we ask: what spatiotemporal patterns of police exist, how do these patterns change over time, and how do these correspond to local crime patterns? Methods Therefore, we analysed more than 77 million GPS signals from 130 police patrol cars and more than 50,000 recorded crimes from 2019.to investigate where and when police patrols are present. All data were geocoded and map matched using high performance computing.Results We found that police, much like crime, concentrates on a small proportion of street segments and that the spatial concentration experiences temporal instability at the micro level. Further, spatiotemporal police presence and its concentration appear to be unrelated to local levels of crime and crime concentration. Conclusions These findings inform police chiefs and researchers alike and enable alterations of patrol deployment in order to refine the spatiotemporal focus of police on local crime. Future considerations are required to research optimal spatiotemporal alignment of police presence to effectively prevent crime.