The Relationship between Neighborhood Characteristics and Homicide in Karachi, Pakistan

Salma Hamza, Imran Khan, Linlin Lu, Hua Liu, Farkhunda Burke, Syed Nawaz-ul-Huda, Muhammad Fahad Baqa and Aqil Tariq
Additional contact information
Salma Hamza: Department of Earth and Environmental Sciences, Bahria University Karachi Campus, Karachi 75300, Pakistan
Imran Khan: Department of Geography, University of Karachi, Karachi 75300, Pakistan
Linlin Lu: Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
Hua Liu: Department of Political Science and Geography, Old Dominion University, Norfolk, VA 23529, USA
Farkhunda Burke: Department of Geography, University of Karachi, Karachi 75300, Pakistan
Syed Nawaz-ul-Huda: Dawn GIS, Geospatial Statistical Research & Analysis Division, Karachi 75300, Pakistan
Muhammad Fahad Baqa: Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
Aqil Tariq: State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS), Wuhan University, Wuhan 430079, China

Sustainability, 2021, vol. 13, issue 10, 1-14

Abstract: The geographical concentration of criminal violence is closely associated with the social, demographic, and economic structural characteristics of neighborhoods. However, few studies have investigated homicide patterns and their relationships with neighborhoods in South Asian cities. In this study, the spatial and temporal patterns of homicide incidences in Karachi from 2009 to 2018 were analyzed using the local indicators of spatial association (LISA) method. Generalized linear modeling (GLM) and geographically weighted Poisson regression (GWPR) methods were implemented to examine the relationship between influential factors and the number of homicides during the 2009–2018 period. The results demonstrate that the homicide hotspot or clustered areas with high homicide counts expanded from 2009 to 2013 and decreased from 2013 to 2018. The number of homicides in the 2017–2018 period had a positive relationship with the percentage of the population speaking Balochi. The unplanned areas with low-density residential land use were associated with low homicide counts, and the areas patrolled by police forces had a significant negative relationship with the occurrence of homicide. The GWPR models effectively characterized the varying relationships between homicide and explanatory variables across the study area. The spatio-temporal analysis methods can be adapted to explore violent crime in other cities with a similar social context.

Keywords: homicide; generalized linear modeling; geographically weighted Poisson regression; neighborhood; Karachi; SDG 11 (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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