Estimates of the parameters used in our dynamic HIV-FGS model (Figure 1).

These parameter estimates produced the best fit of our dynamic model to epidemiological data for HIV and FGS prevalence and co-infection among rural Zimbabwean women [3], [7]. The dynamic model was fit to these data using a Markov Chain Monte Carlo method, which allowed us to calculate distributions of possible values for each of these parameters. We present here the mean of these distributions and their associated 95% credible intervals. The Brooks-Gelman-Rubin (BGR) method was used to monitor convergence of iterative simulations. Convergence was achieved when the upper limit of the credible interval of the BGR diagnostic statistic for a given parameter <1.2 [51].