Abstract
This exploratory study identifies spatial patterns of crimes and their associations with the index of Unsatisfied Basic Needs (UBN), with Communitarian Policy Units (CPU) density, as well as with population density. The case study is the Metropolitan District of Quito. Correlation analyses were applied between number of registers of each type of crime, and the UBN index, CPU density and population density measures. The spatial autocorrelation index of Getis-Ord Gi* was calculated to identify hotspots of the different types of crime. Ordinary least squares regressions and geographically weighted regressions considering types of crime as dependent variables, were calculated. Larceny and robbery were found to be the predominant crimes in the study area. An inverse relationship between the UBN index and number of crimes was identified for each type of crime, while positive relationships were found between crimes and CPU density, and between crimes and population density. Significant hotspots of fraud, homicide, larceny, murder, rape and robbery were found in all urban parishes. Additionally, crime hotspots were identified in eastern rural parishes adjacent to urban parishes. This study provides important implications for crime prevention in the Metropolitan District of Quito (MDQ), and the obtained results contribute to the ecology of crime research in the study area.
Highlights
The identification of spatial patterns of crime is crucial for planning and decision making to protect people and reduce illegal acts
The present study identifies hotspots of crime in the Metropolitan District of Quito (MDQ) mainly located in the urban parishes of the District
These findings are consistent with the work of Dammert and Estrella [43] who carried out a spatial analysis of crime in the urban area of the MDQ using geo-located information from 2006–2008 and found crime concentration in central and northern urban parishes
Summary
The identification of spatial patterns of crime is crucial for planning and decision making to protect people and reduce illegal acts. Crime is spatially and temporally correlated [2], and can be explained by different factors such as population, poverty and police activity. Poverty is a concept relative to what others have [9] and can be more accurate to say that the concept of poverty is associated with the lack of opportunities and services. In this sense, poverty is a condition of not accomplishing basic human rights such as accessing to basic services [10]. The level of poverty can interact with population density to explain crime. Patterson found significant associations between population density and violent crime [9] and argues that increasing population density in more urbanized areas can originate weaker social interactions and lower informal social control
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