This application simulates a stochastic epidemic model of HIV-1 infection to illustrate the impact of sexual partnership concurrency on transmission dynamics. The theory and mathematics of this model are provided in the full Concurrency Tutorial associated with this web application. This model is also built into the EpiModel software available for the R statistical computing platform.

HIV infection is simulated based on a four-stage disease progression model in which persons transition from acute to latent to pre-AIDS to AIDS stages. These transitions occur at deterministic intervals based on estimates of the average time per stage. Also, the transmission probability to uninfected partners varies by stage of the infected partner: it is highest in the acute stage and lowest in the AIDS stage when no sexual acts are simulated to occur. This is based on empirical estimates in Hollingsworth (2008).

These tools were authored by Steven M. Goodreau, Samuel M. Jenness, and Martina Morris