A dynamic bipartite scale-free agent network model for analyzing heterosexual HIV transmission

Individual behaviors, intervention measures and social networks are the key factors influencing the spread of HIV. This paper presents a method based on dynamic bipartite scale-free agent network for investigating HIV heterosexual transmission and the effectiveness of HIV prevention interventions. A bipartite scale-free network configuration generation algorithm is constructed for describing the relationships of heterosexual contacts. Agent describes individual high-risk behavior, course of HIV disease and social structure. Agent also defines the behavior rules for adaption to the HIV prevention interventions. Exploratory simulation results are consistent with empirical studies demonstrating that the effectiveness of a combination of interventions, including voluntary counseling and HIV test, condom promotion for safe sexual behavior and initiating antiretroviral treatment.