title: A stochastic agent-based model of pathogen propagation in dynamic multi-relational social networks.
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 thelocal agencyof 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.
authors: Dept. of Math and Computer Science, John Jay College (CUNY), New York City, New York, USA.
authors: Bilal
authors: B
authors: Khan
authors: Dept. of Sociology, University of Nebraska-Lincoln, Lincoln, Nebraska, USA.
authors: Kirk
authors: K
authors: Dombrowski
authors: NYC Social Network Research Group, John Jay College (CUNY), New York City, New York, USA.
authors: Mohamed
authors: M
authors: Saad