Centers for Disease Control and Prevention, Atlanta, GA.
Department of Epidemiology and Biostatistics, University at Albany, Albany, NY.
Sex Transm Dis. 2019 Jun;46(6):357-363. doi: 10.1097/OLQ.0000000000000980.
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.
背景:性传播感染(STI)会增加人类免疫缺陷病毒(HIV)感染和传播的风险。我们估计了性活跃男男性行为者(MSM)中 HIV 发病率归因于感染两种最常见的细菌性 STI,淋病奈瑟菌(NG)和沙眼衣原体(CT)的比例。
方法:我们使用了一种具有 HIV、NG 和 CT 感染的 MSM 性网络的随机、基于代理的模型。根据 STI 状态,针对感染部位的相对风险(RR)乘数,修改了 HIV 传播和感染的风险。我们估计了 NG 和 CT 对 HIV 发病率的总体影响,以及对 HIV 感染和 HIV 传播的单独影响。每个场景都模拟了 10 年。通过将场景中最后一年的发病率与 RR 与 NG 和 CT 相关的 RR 设置为 1.0 的场景进行比较,确定了每种 RR 组合的人群归因分数(PAF)。
结果:总体而言,10.2%(四分位间距[IQR],7.9-12.4)的 HIV 感染归因于 NG/CT 感染。然后在敏感性分析中,HIV 传播的 PAF 范围从 3.1%(IQR,0.5-5.2)到 20.4%(IQR,17.8-22.5),HIV 感染的 PAF 范围从 2.0%(IQR,-0.7 到 4.3)到 13.8%(IQR,11.7-16.0)。
结论:尽管估计 NG/CT 对 HIV 风险的因果影响存在挑战,但建模是一种替代方法,可以在生物协变量的不确定性下量化可能的影响范围。我们的估计代表了理想化的公共卫生干预措施,在这些干预措施中,可以最大限度地预防 STI,为旨在降低 HIV 发病率的现实世界 STI 干预措施设定目标。
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