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.

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. Results We find that although crime is more concentrated at addresses than other spatial units, this is due to the fact that more addresses have no crime than is true of larger units. When only places with one or more crimes are examined, place crime is no more concentrated than other spatial unit crime. Crime appears to be concentrated at places at about the same level as it is concentrated among offenders or victims. And crime concentration does not appear to be peculiarly concentrated compared to non-crime related phenomena. Conclusions The concentration of crime at places is unexceptional, and should be treated as one manifestation of a general tendency of things to be concentrated.

Interpretations of two bodies of crime-place research conflict. Land use and crime studies claim particular facilities increase crime. Risky facilities studies show most places of a single type have little or no crime, but a few of that type have a great deal of crime. How can a facility be generally criminogenic and mostly safe? To resolve this conflict, we make use of the fact that a single owner can own multiple facilities and each owner may have consistent management practices in their facilities. We first replicate findings of earlier land use studies with crime and land parcel data from Cincinnati. Second, we cluster land parcels by property owners and re-estimate the land use and crime relationship. The links between land use and crime in the replication decline or disappear after clustering. Findings suggest owners’ place management influences crime at their places, thus resolving the conflict between the two bodies of research.

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.