MAP-Centre for Urban Health Solutions, St. Michael's Hospital, Unity Health Toronto.
Institute of Medical Sciences, University of Toronto, Toronto, Ontario.
AIDS. 2021 Jun 1;35(7):1113-1125. doi: 10.1097/QAD.0000000000002826.
HIV pre-exposure prophylaxis (PrEP) may change serosorting patterns. We examined the influence of serosorting on the population-level HIV transmission impact of PrEP, and how impact could change if PrEP users stopped serosorting.
We developed a compartmental HIV transmission model parameterized with bio-behavioural and HIV surveillance data among MSM in Canada.
We separately fit the model with serosorting and without serosorting [counterfactual; sero-proportionate mixing (random partner-selection proportional to availability by HIV status)], and reproduced stable HIV epidemics with HIV-prevalence 10.3-24.8%, undiagnosed fraction 4.9-15.8% and treatment coverage 82.5-88.4%. We simulated PrEP-intervention reaching stable pre-specified coverage by year-one and compared absolute difference in relative HIV-incidence reduction 10 years post-intervention (PrEP-impact) between models with serosorting vs. sero-proportionate mixing; and counterfactual scenarios when PrEP users immediately stopped vs. continued serosorting. We examined sensitivity of results to PrEP-effectiveness (44-99%; reflecting varying dosing or adherence levels) and coverage (10-50%).
Models with serosorting predicted a larger PrEP-impact than models with sero-proportionate mixing under all PrEP-effectiveness and coverage assumptions [median (interquartile range): 8.1% (5.5-11.6%)]. PrEP users' stopping serosorting reduced PrEP-impact compared with when PrEP users continued serosorting: reductions in PrEP-impact were minimal [2.1% (1.4-3.4%)] under high PrEP-effectiveness (86-99%); however, could be considerable [10.9% (8.2-14.1%)] under low PrEP effectiveness (44%) and high coverage (30-50%).
Models assuming sero-proportionate mixing may underestimate population-level HIV-incidence reductions due to PrEP. PrEP-mediated changes in serosorting could lead to programmatically important reductions in PrEP-impact under low PrEP-effectiveness. Our findings suggest the need to monitor sexual mixing patterns to inform PrEP implementation and evaluation.
艾滋病毒暴露前预防（PrEP）可能改变血清学分类模式。我们研究了血清学分类对 PrEP 对人群层面 HIV 传播影响的影响，以及如果 PrEP 用户停止血清学分类，影响会如何变化。
我们使用加拿大男男性行为者的生物行为和 HIV 监测数据，开发了一个包含 HIV 传播的隔室模型。
我们分别使用血清学分类和不使用血清学分类（对照；血清比例混合（根据 HIV 状态按供应情况随机选择性伴侣））拟合模型，并使用 HIV 流行率为 10.3-24.8%、未确诊率为 4.9-15.8%和治疗覆盖率为 82.5-88.4%的模型再现稳定的 HIV 流行。我们模拟了 PrEP 干预措施，在第一年达到稳定的预定义覆盖率，并比较了血清学分类模型与血清比例混合模型在干预后 10 年相对 HIV 发病率降低的绝对差异（PrEP 效果）；以及当 PrEP 用户立即停止与继续血清学分类时的对照情况。我们研究了 PrEP 效果（44-99%；反映不同的剂量或依从水平）和覆盖率（10-50%）对结果的敏感性。
在所有 PrEP 效果和覆盖率假设下，血清学分类模型预测的 PrEP 效果大于血清比例混合模型[中位数（四分位距）：8.1%（5.5-11.6%）]。与 PrEP 用户继续血清学分类相比，PrEP 用户停止血清学分类会降低 PrEP 的效果：在高 PrEP 效果（86-99%）下，降低幅度较小[2.1%（1.4-3.4%）]；然而，在低 PrEP 效果（44%）和高覆盖率（30-50%）下，降低幅度可能较大[10.9%（8.2-14.1%）]。
假设血清比例混合的模型可能低估了 PrEP 导致的人群层面 HIV 发病率降低。PrEP 介导的血清学分类变化可能导致 PrEP 效果在低 PrEP 效果下显著降低。我们的研究结果表明，需要监测性混合模式，为 PrEP 的实施和评估提供信息。
