Héctor Sánchez-Delgado

Objectives: We analyze street-segment-level property crime trends in Barcelona from 2010 to 2018 using group-based trajectory modeling (GBTM), with two main goals: to assess the applicability of the law of crime concentration in a European context, and to investigate the temporal stability of hot, cool, and cold spots. Methods: GBTM is implemented using a Zero-Inflated Poisson (ZIP) model to account for over-dispersion, identifying latent trajectory groups. A post-hoc validation is conducted through: (a) comparison with time-series clustering to assess alignment, and (b) an analysis of posterior probability distributions to evaluate classification robustness. Results: Nine distinct crime trajectory groups are identified. Three of these groups, which together include just 1% of street segments, account for nearly 30% of total property crimes. While fluctuations occur among groups, the dominance of a small fraction of high-crime street segments remains, confirming the concentration of crime in specific areas. Notably, some hot and cool spots exhibit increasing trends, pointing to the emergence of new crime areas. A strong nested relationship between GBTM groups and time-series clusters further reinforces the validity of the classification. Posterior probability distributions also show clear separation among groups. Conclusions: This study supports the law of crime concentration in Barcelona while revealing specific local dynamics that differ from those found in North American cities. It demonstrates the effectiveness of combining GBTM with post-hoc analysis to examine micro-level crime patterns, offering a transferable methodological framework for other urban contexts. These findings have important implications for crime prevention and urban policy in European settings.

This article focuses on the study of the impact of the environment and its characteristics on criminal incidence, a central theme in Spatial Criminology. The Social Disorganization Theory (SDT) and the Routine Activities Theory (RAT), both belonging to Spatial Criminology and in competition, address the question of what spatial factors influence crime but from different perspectives (ecological and environmental, respectively). The research explores the contribution and importance of explanatory variables from both theories, as well as their combination to enhance the explanation of spatial variability in crime. Using Negative Binomial Regression for various criminal typologies and years, utilizing census tracts as the geographical unit, the results emphasize the need to integrate these theories to more effectively model criminal variability among census tracts. Additionally, it is observed that these theories offer distinct explanatory capacity depending on the criminal typology considered. Este artículo se centra en el estudio del impacto del entorno y sus características en la incidencia delictiva, un tema central en la Criminología Espacial. La Teoría de la Desorganización Social (TDS) y la de las Actividades Cotidianas (TAC), ambas pertenecientes al paradigma de la Criminología Espacial y en competencia, abordan la pregunta de qué factores espaciales afectan al delito, perodesde diferentes perspectivas (ecológica y ambiental, respectivamente). La investigación explora la contribución e importancia de variables de ambas teorías, así como su combinación para mejorar la explicación de la variabilidad espacial del delito. Mediante el uso de la Regresión de la Binomial Negativa para diversas tipologías delictivas y años, utilizando la sección censal como unidad geográfica, los resultados destacan la necesidad de integrar estas teorías para modelar de manera más efectiva la variabilidad delictiva entre secciones censales. Además, se observa que estas teorías presentan una capacidad explicativa distinta dependiendo de la tipología delictiva.