Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.
Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.
Lancet HIV. 2022 Nov;9(11):e771-e780. doi: 10.1016/S2352-3018(22)00259-4.
BACKGROUND: The long-term impact of universal home-based testing and treatment as part of universal testing and treatment (UTT) on HIV incidence is unknown. We made projections using a detailed individual-based model of the effect of the intervention delivered in the HPTN 071 (PopART) cluster-randomised trial. METHODS: In this modelling study, we fitted an individual-based model to the HIV epidemic and HIV care cascade in 21 high prevalence communities in Zambia and South Africa that were part of the PopART cluster-randomised trial (intervention period Nov 1, 2013, to Dec 31, 2017). The model represents coverage of home-based testing and counselling by age and sex, delivered as part of the trial, antiretroviral therapy (ART) uptake, and any changes in national guidelines on ART eligibility. In PopART, communities were randomly assigned to one of three arms: arm A received the full PopART intervention for all individuals who tested positive for HIV, arm B received the intervention with ART provided in accordance with national guidelines, and arm C received standard of care. We fitted the model to trial data twice using Approximate Bayesian Computation, once before data unblinding and then again after data unblinding. We compared projections of intervention impact with observed effects, and for four different scenarios of UTT up to Jan 1, 2030 in the study communities. FINDINGS: Compared with standard of care, a 51% (95% credible interval 40-60) reduction in HIV incidence is projected if the trial intervention (arms A and B combined) is continued from 2020 to 2030, over and above a declining trend in HIV incidence under standard of care. INTERPRETATION: A widespread and continued commitment to UTT via home-based testing and counselling can have a substantial effect on HIV incidence in high prevalence communities. FUNDING: National Institute of Allergy and Infectious Diseases, US President's Emergency Plan for AIDS Relief, International Initiative for Impact Evaluation, Bill & Melinda Gates Foundation, National Institute on Drug Abuse, and National Institute of Mental Health.
背景：作为普遍检测和治疗（UTT）的一部分，普及家庭检测和治疗对艾滋病毒发病率的长期影响尚不清楚。我们使用 HPTN 071（PopART）群组随机试验中干预措施的详细个体模型进行了预测。
方法：在这项建模研究中，我们将个体模型拟合到赞比亚和南非 21 个高流行社区的艾滋病毒流行和艾滋病毒护理级联中，这些社区是 PopART 群组随机试验的一部分（干预期为 2013 年 11 月 1 日至 2017 年 12 月 31 日）。该模型代表了作为试验一部分提供的家庭检测和咨询的年龄和性别覆盖率、抗逆转录病毒治疗（ART）的采用率以及国家 ART 资格标准的任何变化。在 PopART 中，社区被随机分配到三个组中的一个：A 组接受所有艾滋病毒检测呈阳性者的完整 PopART 干预，B 组接受符合国家指南的干预措施和 ART，C 组接受标准护理。我们使用近似贝叶斯计算对模型进行了两次拟合，一次在数据未公开之前，一次在数据未公开之后。我们比较了干预效果的预测值与观察到的效果，并对研究社区中四种不同的 UTT 方案（直至 2030 年 1 月 1 日）进行了比较。
结果：与标准护理相比，如果从 2020 年到 2030 年继续进行试验干预（A 组和 B 组相结合），预计艾滋病毒发病率将降低 51%（95%置信区间为 40-60%），这超过了标准护理下艾滋病毒发病率的下降趋势。
解释：通过家庭检测和咨询广泛而持续地承诺 UTT，可以对高流行社区的艾滋病毒发病率产生重大影响。
资金：美国国家过敏和传染病研究所、美国总统艾滋病紧急救援计划、国际影响评估倡议、比尔和梅林达盖茨基金会、美国国立药物滥用研究所和美国国家心理健康研究所。
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