Background: Despite the increasing awareness and interests about the importance of crime concentration at places, scholars have not comprehensively synthesized the body of evidence related to this thesis. We conduct a systematic review and meta-analysis of the evidence that crime is concentrated among places. Methods:We identified 44 studies that empirically examined crime concentration at place and provided quantitative information sufficient for analysis. We organized data using visual binning and fitted logarithmic curves to the median values of the bins. We examine concentration in two conditions: when all places are studied (prevalence), and when only places with at least one crime are studied (frequency). Results:We find that crime is concentrated at a relatively few places in both conditions. We also compared concentration for calls for services to reported crime incidents. Calls for services appear more concentrated than crime at places. Because there are several ways place is defined, we compared different units of analysis. Crime is more concentrated at addresses than other units, including street segments. We compared crime concentration over time and found less concentration in 2000s compared to 1980s and 1990s. We also compared crime concentration between U.S. and non-U.S. countries and found more concentration in U.S. Finally, violent crime is more concentrated than property crime. Conclusions:Though we systematically reviewed a comprehensive list of studies, summarizing this literature is problematic. Not only should more systematic reviews be conducted as more research becomes available, but future inquiries should examine other ways of summarizing these studies that could challenge our findings.

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Background: Numerous studies have established that crime is highly concentrated among a small group of offenders. These findings have guided the development of various crime prevention strategies. The underlying theme of these strategies is that by focusing on the few offenders who are responsible for most of the crime, we can prevent the greatest amount of crime with the fewest resources. Nevertheless, there has been no systematic review of the many studies, so it is possible that the accepted understanding among researchers and practitioners is based on a few prominent studies that are misleading. Further, we do not know how concentrated crime is among offenders, given the variety of ways researchers report their findings. This paper systematically reviews this literature and uses meta-analysis to determine how confident we can be that crime is concentrated among a few offenders. Methods:We first systematically reviewed the literature and found 73 studies on the concentration of crime among offenders. From those studies, we identified 15 studies on the prevalence of offending and 27 studies on the frequency of offending that provided data suitable for analysis. We then performed a meta-analysis of those studies to examine how crime is concentrated among the worst offenders and how that concentration varies between different types of offenders. Results:We found that crime is highly concentrated in the population and across different types of offenders. Little variation in concentration exists between youths and adults or between American offenders and those from other countries. We found more variation between males and females in the concentration of offending, though we believe this may be due to the more limited data on female offenders. Conclusions:The systematic review and meta-analysis we present here is the first study of its kind on offending concentration. This is an important step in closing this gap in the crime prevention literature, but we encourage making updates to this systematic review as new literature becomes available, and using alternate methods of summarizing these studies that could challenge these findings.

Real-time crime hot spot forecasting presents challenges to policing. There is a high volume of hot spot misclassifications and a lack of theoretical support for forecasting algorithms, especially in disciplines outside the fields of criminology and criminal justice. Transparency is particularly important as most hot spot forecasting models do not provide their underlying mechanisms. To address these challenges, we operationalize two different theories in our algorithm to forecast crime hot spots over Portland and Cincinnati. First, we use a population heterogeneity framework to find places that are consistent hot spots. Second, we use a state dependence model of the number of crimes in the time periods prior to the predicted month. This algorithm is implemented in Excel, making it extremely simple to apply and completely transparent. Our forecasting models show high accuracy and high efficiency in hot spot forecasting in both Portland and Cincinnati context. We suggest previously developed hot spot forecasting models need to be reconsidered.

Background: That crime is concentrated at a few places is well established by over 44 studies. This is true whether one examines addresses or street segments. Additionally, crime is concentrated among offenders and victims. Many physical, biological, and social phenomena are concentrated as well. This raises a question: is crime more or less concentrated at places than other phenomena? If it is not, then crime concentration maybe the result of standard ubiquitous processes that operate in nature. If crime is more or is less concentrated than other phenomena, then researchers need to ask why. Methods:We synthesize results from three systematic reviews and review other literatures to provide preliminary answers.