A stochastic agent-based model of pathogen propagation in dynamic multi-relational social networks

Research output: Contribution to journalArticle

9 Scopus citations


We describe a general framework for modeling and stochastic simulation of epidemics in realistic dynamic social networks, which incorporates heterogeneity in the types of individuals, types of interconnecting risk-bearing relationships, and types of pathogens transmitted across them. Dynamism is supported through arrival and departure processes, continuous restructuring of risk relationships, and changes to pathogen infectiousness, as mandated by natural history; dynamism is regulated through constraints on the local agency of individual nodes and their risk behaviors, while simulation trajectories are validated using system-wide metrics. To illustrate its utility, we present a case study that applies the proposed framework towards a simulation of HIV in artificial networks of intravenous drug users (IDUs) modeled using data collected in the Social Factors for HIV Risk survey.

Original languageEnglish (US)
Pages (from-to)460-484
Number of pages25
Issue number4
StatePublished - Apr 2014



  • Agent-based systems
  • Social Factors for HIV Risk
  • modeling and simulation environments
  • network-based simulation
  • risk network
  • system dynamics

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation
  • Computer Graphics and Computer-Aided Design

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