Using a transmission dynamic model to estimate annual HIV incidence rate among drug users in China

Objective To estimate annual human immunodeficiency virus (HIV) incidence rate among drug users in China from 1995 to 2014 based on a transmission dynamic model. Methods An HIV transmission dynamic model was developed to describe the HIV epidemic among drug users in China. The model was parameterized using data from literature available. The incidence rate was estimated through Bayesian melding approach achieved by Monte Carlo simulation after training and testing the model based on HIV prevalence data from national sentinel sites. Results The trained model consisting of three compartments (susceptible, HIV infected and AIDS patients) predicted HIV prevalence precisely with small average relative error(4.37%).The model-predicted HIV prevalence fitted well to HIV prevalence data (R²=0.89, P<0.001). HIV incidence rate predicted by the model peaked in 1996(4.06%), then decreased to 1.25% in 2000. It rose again to 1.95% in 2002 and continued to decrease until around 2008 to 2014 when it leveled off between 0.50% and 0.90%. Conclusions The model was able to attain a good fit to HIV prevalence data, allowing for reasonably precise estimate of the incidence rate, which showed that HIV comprehensive prevention and control measures in China had positive impact on reducing HIV incidence rate among drug users.