April M Zeoli1, Sue Grady1, Jesenia M Pizarro1, Chris Melde1. 1. April M. Zeoli, Jesenia M. Pizarro, and Chris Melde are with the School of Criminal Justice, Michigan State University, East Lansing. Sue Grady is with the Department of Geography, Michigan State University.
Abstract
OBJECTIVES: We modeled the spatiotemporal movement of hotspot clusters of homicide by motive in Newark, New Jersey, to investigate whether different homicide types have different patterns of clustering and movement. METHODS: We obtained homicide data from the Newark Police Department Homicide Unit's investigative files from 1997 through 2007 (n = 560). We geocoded the address at which each homicide victim was found and recorded the date of and the motive for the homicide. We used cluster detection software to model the spatiotemporal movement of statistically significant homicide clusters by motive, using census tract and month of occurrence as the spatial and temporal units of analysis. RESULTS: Gang-motivated homicides showed evidence of clustering and diffusion through Newark. Additionally, gang-motivated homicide clusters overlapped to a degree with revenge and drug-motivated homicide clusters. Escalating dispute and nonintimate familial homicides clustered; however, there was no evidence of diffusion. Intimate partner and robbery homicides did not cluster. CONCLUSIONS: By tracking how homicide types diffuse through communities and determining which places have ongoing or emerging homicide problems by type, we can better inform the deployment of prevention and intervention efforts.
OBJECTIVES: We modeled the spatiotemporal movement of hotspot clusters of homicide by motive in Newark, New Jersey, to investigate whether different homicide types have different patterns of clustering and movement. METHODS: We obtained homicide data from the Newark Police Department Homicide Unit's investigative files from 1997 through 2007 (n = 560). We geocoded the address at which each homicide victim was found and recorded the date of and the motive for the homicide. We used cluster detection software to model the spatiotemporal movement of statistically significant homicide clusters by motive, using census tract and month of occurrence as the spatial and temporal units of analysis. RESULTS: Gang-motivated homicides showed evidence of clustering and diffusion through Newark. Additionally, gang-motivated homicide clusters overlapped to a degree with revenge and drug-motivated homicide clusters. Escalating dispute and nonintimate familial homicides clustered; however, there was no evidence of diffusion. Intimate partner and robbery homicides did not cluster. CONCLUSIONS: By tracking how homicide types diffuse through communities and determining which places have ongoing or emerging homicide problems by type, we can better inform the deployment of prevention and intervention efforts.
Authors: Uma Raman; Philip A Bonanno; Devika Sachdev; Aparna Govindan; Atharva Dhole; Oluwafeyijimi Salako; Jay Patel; Lama R Noureddine; Jessica Tu; Jenieve Guevarra-Fernández; Ashley Leto; Christopher Nemeh; Aesha Patel; Alexis Nicheporuck; Ashley Tran; Cheryl A Kennedy Journal: Community Ment Health J Date: 2020-07-31
Authors: David A Larsen; Sandra Lane; Timothy Jennings-Bey; Arnett Haygood-El; Kim Brundage; Robert A Rubinstein Journal: PLoS One Date: 2017-03-20 Impact factor: 3.240