4.5 Article

Linking Neighborhood Characteristics and Drug-Related Police Interventions: A Bayesian Spatial Analysis

Journal

Publisher

MDPI
DOI: 10.3390/ijgi6030065

Keywords

drug-related police interventions; neighborhoods; Bayesian spatial modeling; small-area variations; risk maps

Funding

  1. Spanish Ministerio de Economia y Competitividad [PSI2014-54561-P]
  2. FPU program of the Spanish Ministerio de Educacion, Cultura y Deporte [FPU2013/00164]

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This paper aimed to analyze the spatial distribution of drug-related police interventions and the neighborhood characteristics influencing these spatial patterns. To this end, police officers ranked each census block group in Valencia, Spain (N = 552), providing an index of drug-related police interventions. Data from the City Statistics Office and observational variables were used to analyze neighborhood characteristics. Distance to the police station was used as the control variable. A Bayesian ecological analysis was performed with a spatial beta regression model. Results indicated that high physical decay, low socioeconomic status, and high immigrant concentration were associated with high levels of drug-related police interventions after adjustment for distance to the police station. Results illustrate the importance of a spatial approach to understanding crime.

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