The Impact of Violence Interruption on the Diffusion of Violence: A Mathematical Modeling Approach

Conference paper
Part of the Association for Women in Mathematics Series book series (AWMS, volume 6)


Public health approaches to interrupting infectious disease transmission have yet to be informed by traditional deterministic models of contagion. We investigate this gap in current violence prevention research by introducing a Susceptible–Transmitter–Victim Epidemic model, based on the classic Susceptible–Infectious–Recovered differential equation model, to explore the impact of violence interruption on the diffusion of violence. Uncertainty and sensitivity analysis are done using Latin hypercube sampling. Based on sensitivity analysis results, model predictions appear to be overestimating annual gun assault cases, where the mean estimate of the gun assault rate at equilibrium is double the average gun assault rate over the past decade. Several key parameters are identified as significant to gun assault predictions and may account for model imprecision. Scenario analysis is also done to determine the effectiveness of violence interruption programs. Results suggest that targeting all potential violence transmitters can reduce gun violence three times more than an intervention that only targets gun-owning individuals, indicating the importance of taking a holistic approach to violence interruption and prevention. Our results also suggest that having individuals in the population transmitting violence, whether or not they are participating in gun violence, is sufficient to sustain a gun violence epidemic.


Contagious violence Infectious disease model Violence interruption Gun violence 

Mathematics Subject Classification




The authors would like to thank the reviewers for their very thorough comments that were used to improve the manuscript.

This work was supported by the National Institute of Alcohol Abuse and Alcoholism,, grant number R01AA020331-01A1 and the Center for Disease Control and Prevention,, Center grant R49CE002474.

The authors declare that no competing financial interests exist.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Department of Biostatistics and EpidemiologyUniversity of PennsylvaniaPhiladelphiaUSA
  2. 2.Department of MathematicsHampton UniversityHamptonUSA

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