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Paper Submitted: Journal of Artificial Societies and Social Simulation

Modeling Dynamic Risk Networks
We describe a general framework for stochastic actor-based modeling of real-world dynamic risk networks. The models capture heterogeneity in the types of individuals, their interconnecting risk relationships, and the pathogens flowing between them. Dynamism is supported through arrival and departure processes, continuous restructuring of risk relationships, and changes to the pathogen over its lifetime. Whenever possible, the system is regulated through constraints on the local agency of individual nodes, risk relationships, and pathogen flows, rather than by system-wide specifications. We illustrate the application of the framework by applying it to a case study of HIV prevalence in injecting drug user (IDU) networks in New York City.
Khan, Dombrowski, Saad