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Original Investigation
Firearm Violence
March 2017

Modeling Contagion Through Social Networks to Explain and Predict Gunshot Violence in Chicago, 2006 to 2014

Author Affiliations
  • 1John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts
  • 2Department of Sociology, Yale University, New Haven, Connecticut
  • 3Yale Institute for Network Science, Yale University, New Haven, Connecticut
JAMA Intern Med. 2017;177(3):326-333. doi:10.1001/jamainternmed.2016.8245
Key Points

Question  Does gun violence spread over social networks through a process of social contagion?

Findings  An epidemiological analysis of a network of 138 163 individuals in Chicago, Illinois, determined that social contagion was responsible for 63.1% of the 11 123 gunshot violence episodes that occurred between 2006 and 2014. Models incorporating social contagion and demographics (eg, age, sex, and neighborhood residence) predicted future gunshot subjects better than models based on social contagion or demographics alone.

Meaning  Violence prevention efforts that account for social contagion, in addition to demographics, have the potential to prevent more shootings than efforts that focus only on demographics.

Abstract

Importance  Every day in the United States, more than 200 people are murdered or assaulted with a firearm. Little research has considered the role of interpersonal ties in the pathways through which gun violence spreads.

Objective  To evaluate the extent to which the people who will become subjects of gun violence can be predicted by modeling gun violence as an epidemic that is transmitted between individuals through social interactions.

Design, Setting, and Participants  This study was an epidemiological analysis of a social network of individuals who were arrested during an 8-year period in Chicago, Illinois, with connections between people who were arrested together for the same offense. Modeling of the spread of gunshot violence over the network was assessed using a probabilistic contagion model that assumed individuals were subject to risks associated with being arrested together, in addition to demographic factors, such as age, sex, and neighborhood residence. Participants represented a network of 138 163 individuals who were arrested between January 1, 2006, and March 31, 2014 (29.9% of all individuals arrested in Chicago during this period), 9773 of whom were subjects of gun violence. Individuals were on average 27 years old at the midpoint of the study, predominantly male (82.0%) and black (75.6%), and often members of a gang (26.2%).

Main Outcomes and Measures  Explanation and prediction of becoming a subject of gun violence (fatal or nonfatal) using epidemic models based on person-to-person transmission through a social network.

Results  Social contagion accounted for 63.1% of the 11 123 gunshot violence episodes; subjects of gun violence were shot on average 125 days after their infector (the person most responsible for exposing the subject to gunshot violence). Some subjects of gun violence were shot more than once. Models based on both social contagion and demographics performed best; when determining the 1.0% of people (n = 1382) considered at highest risk to be shot each day, the combined model identified 728 subjects of gun violence (6.5%) compared with 475 subjects of gun violence (4.3%) for the demographics model (53.3% increase) and 589 subjects of gun violence (5.3%) for the social contagion model (23.6% increase).

Conclusions and Relevance  Gunshot violence follows an epidemic-like process of social contagion that is transmitted through networks of people by social interactions. Violence prevention efforts that account for social contagion, in addition to demographics, have the potential to prevent more shootings than efforts that focus on only demographics.

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