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通过扩大获得抗逆转录病毒疗法的机会来消除南非的艾滋病毒:模型比较研究。

Elimination of HIV in South Africa through expanded access to antiretroviral therapy: a model comparison study.

机构信息

Department of Public Health, Erasmus MC-University Medical Center Rotterdam, Rotterdam, Netherlands ; Nijmegen International Center for Health System Analysis and Education, Department of Primary and Community Care, Radboud University Nijmegen Medical Centre, Nijmegen, Netherlands ; Africa Centre for Health and Population Studies, University of KwaZulu-Natal, Mtubatuba, South Africa.

出版信息

PLoS Med. 2013 Oct;10(10):e1001534. doi: 10.1371/journal.pmed.1001534. Epub 2013 Oct 22.

DOI:10.1371/journal.pmed.1001534
PMID:24167449
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3805487/
Abstract

BACKGROUND

Expanded access to antiretroviral therapy (ART) using universal test and treat (UTT) has been suggested as a strategy to eliminate HIV in South Africa within 7 y based on an influential mathematical modeling study. However, the underlying deterministic model was criticized widely, and other modeling studies did not always confirm the study's finding. The objective of our study is to better understand the implications of different model structures and assumptions, so as to arrive at the best possible predictions of the long-term impact of UTT and the possibility of elimination of HIV.

METHODS AND FINDINGS

We developed nine structurally different mathematical models of the South African HIV epidemic in a stepwise approach of increasing complexity and realism. The simplest model resembles the initial deterministic model, while the most comprehensive model is the stochastic microsimulation model STDSIM, which includes sexual networks and HIV stages with different degrees of infectiousness. We defined UTT as annual screening and immediate ART for all HIV-infected adults, starting at 13% in January 2012 and scaled up to 90% coverage by January 2019. All models predict elimination, yet those that capture more processes underlying the HIV transmission dynamics predict elimination at a later point in time, after 20 to 25 y. Importantly, the most comprehensive model predicts that the current strategy of ART at CD4 count ≤350 cells/µl will also lead to elimination, albeit 10 y later compared to UTT. Still, UTT remains cost-effective, as many additional life-years would be saved. The study's major limitations are that elimination was defined as incidence below 1/1,000 person-years rather than 0% prevalence, and drug resistance was not modeled.

CONCLUSIONS

Our results confirm previous predictions that the HIV epidemic in South Africa can be eliminated through universal testing and immediate treatment at 90% coverage. However, more realistic models show that elimination is likely to occur at a much later point in time than the initial model suggested. Also, UTT is a cost-effective intervention, but less cost-effective than previously predicted because the current South African ART treatment policy alone could already drive HIV into elimination. Please see later in the article for the Editors' Summary.

摘要

背景

基于一项有影响力的数学模型研究,扩大抗逆转录病毒疗法(ART)的普及,即普遍检测和治疗(UTT),被认为是南非在 7 年内消除艾滋病毒的一种策略。然而,该研究的基本确定性模型受到了广泛的批评,其他建模研究并不总是证实该研究的发现。我们研究的目的是更好地理解不同模型结构和假设的含义,以便对 UTT 的长期影响和消除 HIV 的可能性做出最佳预测。

方法和发现

我们采用逐步增加复杂性和现实性的方法,开发了九个不同结构的南非艾滋病毒流行数学模型。最简单的模型类似于初始确定性模型,而最全面的模型是随机微观模拟模型 STDSIM,该模型包括具有不同传染性程度的性网络和 HIV 阶段。我们将 UTT 定义为每年对所有感染艾滋病毒的成年人进行筛查,并立即进行 ART,从 2012 年 1 月的 13%开始,到 2019 年 1 月扩大到 90%的覆盖率。所有模型都预测了消除,但那些更能捕捉艾滋病毒传播动力学背后过程的模型预测消除将在更晚的时间点发生,在 20 到 25 年后。重要的是,最全面的模型预测,目前按照 CD4 计数≤350 个细胞/μl 进行 ART 的策略也将导致消除,尽管比 UTT 晚 10 年。尽管如此,UTT 仍然具有成本效益,因为会挽救更多的生命年。本研究的主要局限性是,消除的定义是发病率低于 1/1000 人年,而不是 0%的患病率,并且没有建模药物耐药性。

结论

我们的研究结果证实了先前的预测,即南非的艾滋病毒流行可以通过普遍检测和 90%覆盖率的立即治疗来消除。然而,更现实的模型表明,消除可能发生在比初始模型建议的时间晚得多的时间点。此外,UTT 是一种具有成本效益的干预措施,但不如以前预测的那么具有成本效益,因为南非目前的 ART 治疗政策本身就可以使 HIV 消除。请稍后在文章中查看编辑摘要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17b6/3805487/9c8ac9c1cd44/pmed.1001534.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17b6/3805487/131bb4968495/pmed.1001534.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17b6/3805487/01461d7ff9ce/pmed.1001534.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17b6/3805487/581b51f76a43/pmed.1001534.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17b6/3805487/9c8ac9c1cd44/pmed.1001534.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17b6/3805487/131bb4968495/pmed.1001534.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17b6/3805487/01461d7ff9ce/pmed.1001534.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17b6/3805487/581b51f76a43/pmed.1001534.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/17b6/3805487/9c8ac9c1cd44/pmed.1001534.g004.jpg

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