Social Disorganization and Urban Homicide Rates: A Spatial-Temporal Analysis in São Paulo, Brazil 2000 to 2015

Amy Nivette*, Maria Fernanda Tourinho Peres

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

This study aims to contribute to understanding urban spatial and temporal patterns of social disorganization and homicide rates in São Paulo, Brazil (2000–2015). Using exploratory spatial data analysis and spatial panel regression techniques, we describe spatial-temporal patterns of homicide rates and assess to what extent social disorganization can explain between-district variation in homicide trajectories. The results showed some variation in the pattern of homicide decline across districts, and less disorganized communities experienced earlier, more linear declines. However, we found no evidence to suggest that changes in social disorganization are associated with differences in the decline in homicide rates.

Original languageEnglish
Pages (from-to)219–243
Number of pages25
JournalHomicide Studies
Volume26
Issue number3
Early online date19 Apr 2021
DOIs
Publication statusPublished - Aug 2022

Bibliographical note

Funding Information:
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This project is funded by The Brazilian National Council for Scientific and Technological Development (Award number: 423550/2016-0).

Publisher Copyright:
© 2021 SAGE Publications.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This project is funded by The Brazilian National Council for Scientific and Technological Development (Award number: 423550/2016-0).

Keywords

  • homicide decline
  • mapping
  • social disorganization
  • spatial analysis
  • structural correlates
  • trends

Fingerprint

Dive into the research topics of 'Social Disorganization and Urban Homicide Rates: A Spatial-Temporal Analysis in São Paulo, Brazil 2000 to 2015'. Together they form a unique fingerprint.

Cite this