In recent years, various academic studies have proposed crime forecasting models based on the concept of repeat victimization. Some of them have been modelled from the area of differential equations and others from the perspective of spatio-temporal statistics, within the framework of point processes. These models have tended towards a certain sophistication in their formulation, which at times impedes understanding of the predictive mechanism and how it adapts to different realities. Predictive models that function well in one environment or society do not appear to do so in others. In this article, the possibility of crime forecasting for burglaries with forced entry in Catalonia is studied from the perspective of near repeat victimization on a larger territorial scale than is usual. To this effect, the explicative and predictive possibilities of this criminological theory are explored and a predictive system that does not require mathematical or statistical models is proposed. We found that a large part of the series of burglaries with forced entry in residences in Catalonia between 2014 and 2015 follow patterns of near repeat victimization. In addition, the average intensity of burglaries in space–time was high, as was the standard deviation. This system is adaptable to different environments and gives police forces the opportunity to improve preventative strategies and to optimize resources using standard tools. Last, the limitations of this approach are debated and new lines of investigation proposed that could increase its predictive capacity without abandoning the concept of repeat victimization.
Evaluating the Impact the Weekday Has on Near-Repeat Victimization: A Spatio-Temporal Analysis of Street Robberies in the City of Vienna, Austria