Background: Sexually transmitted infections (STIs) are associated with an increased risk of human immunodeficiency virus (HIV) acquisition and transmission. We estimated the proportion of HIV incidence among men who have sex with men attributable to infection with the 2 most common bacterial STIs, Neisseria gonorrhoeae (NG) and Chlamydia trachomatis (CT).
Methods: We used a stochastic, agent-based model of a sexual network of MSM with cocirculating HIV, NG, and CT infections. Relative risk (RR) multipliers, specific to anatomic site of infection, modified the risk of HIV transmission and acquisition based on STI status. We estimated the effect of NG and CT on HIV incidence overall and on HIV acquisition and HIV transmission separately. Each scenario was simulated for 10 years. The population attributable fraction (PAF) was determined for each combination of RRs by comparing the incidence in the final year of a scenario to a scenario in which the RRs associated with NG and CT were set to 1.0.
Results: Overall, 10.2% (interquartile range [IQR], 7.9-12.4) of HIV infections were attributable to NG/CT infection. Then in sensitivity analyses, the PAF for HIV transmission ranged from 3.1% (IQR, 0.5-5.2) to 20.4% (IQR, 17.8-22.5) and the PAF for HIV acquisition ranged from 2.0% (IQR, -0.7 to 4.3) to 13.8% (IQR, 11.7-16.0).
Conclusions: Despite challenges in estimating the causal impact of NG/CT on HIV risk, modeling is an alternative approach to quantifying plausible ranges of effects given uncertainty in the biological cofactors. Our estimates represent idealized public health interventions in which STI could be maximally prevented, setting targets for real-world STI interventions that seek to reduce HIV incidence.