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

Authored by Bilal Khan, Kirk Dombrowski, Mohamed Saad

Date Published: 2014-04

DOI: 10.1177/0037549714526947

Sponsors: United States National Institutes of Health (NIH)

Platforms: No platforms listed

Model Documentation: Other Narrative Mathematical description

Model Code URLs: Model code not found

Abstract

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.

Tags

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