How to reach the last milestone for HIV elimination in Africa: a data-based mapping approach.
How to reach the last milestone for HIV elimination in Africa: a data-based mapping approach.
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如何实现非洲消除艾滋病毒的最后一个里程碑：基于数据的绘图方法。
DOI：
10.1016/s2214-109x(23)00243-7
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发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Blower,Sally
中科院分区：
文献类型：
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作者：
Okano,JustinT;Low,Andrea;Ndagije,Felix;Dullie,Luckson;Blower,Sally
联合国艾滋病规划署制定了到2030年消除艾滋病毒的目标：诊断95%的艾滋病毒携带者，治疗95%的确诊患者，并在95%的接受治疗的患者中实现病毒抑制。1撒哈拉以南非洲的几个国家似乎相当接近实现治疗和病毒抑制目标，但在实现诊断目标方面不太成功。2、3除非达到最后这一目标，否则将不可能获得消除所需的高治疗覆盖率和病毒抑制水平。在这里，我们讨论如何通过使用基于数据的映射方法来找到未诊断的艾滋病毒携带者，从而实现最后一个目标。我们提议的方法能够确定全国确诊比例的地理差异，确定未诊断的艾滋病毒携带者的地理位置，并估计有多少未诊断的人生活在这些地区。我们通过将我们的方法应用于莱索托来展示我们方法的有效性，莱索托是南非的一个多山的内陆国家(图A)，到2016-17年，莱索托已经诊断出81%的艾滋病毒感染者，为92%的人提供了治疗，并在88%的接受治疗的人中实现了病毒抑制。4为了实施该方法，需要两种类型的数据：关于诊断水平的地理参考数据和时间上并发的、高分辨率的网格化人口数据。必要的人口数据可从世界流行数据库5公开获得，必要的诊断数据可从人口艾滋病毒影响评估调查中获得；这些调查在14个非洲国家进行。PHIA调查的目的是估计这些国家距离实现联合国艾滋病规划署的治疗目标有多近。2015年至2019年期间进行了6次PHIA1调查；自2019年末以来一直在进行PHIA2调查。PHIA是具有全国代表性的横断面研究；在莱索托进行的PHIA称为LePHIA。每个PHIA都基于两阶段整群抽样策略。在每个群中随机抽取7个个体，然后将其地理定位到群的质心。然后，这些集群在地理上被移位(即，屏蔽)以确保匿名性。7 PHIA收集了关于艾滋病毒检测、艾滋病毒服务的接受和坚持治疗的详细个人信息。参与者回答了问卷，并提供了生物特征数据，这些数据与他们的问卷相关联。血液样本被用来确定每个人的艾滋病毒状况，并(在艾滋病毒携带者中)定量评估病毒载量和检测抗逆转录病毒药物。如果艾滋病毒携带者意识到他们被感染了，或者如果在他们的血液中检测到抗逆转录病毒药物，他们就被认为是确诊的。为了量化全国艾滋病毒诊断比例的地理差异，我们使用了LePHIA1(2016和2017年收集的)数据来估计每个群集点被诊断为艾滋病毒携带者的百分比。我们
UNAIDS has set targets to eliminate HIV by 2030: diagnose 95% of people living with HIV, treat 95% of diagnosed individuals, and attain viral suppression in 95% of treated individuals. 1 Several countries in sub-Saharan Africa appear fairly close to achieving the treatment and viral suppression targets, but have been less successful in achieving the diagnosis target. 2, 3 Unless this last target is reached, the high treatment coverage and level of viral suppression needed for elimination will be impossible to obtain. Here, we discuss how to reach this last target by using a data-based mapping approach to find undiagnosed people living with HIV. Our proposed approach enables the identification of countrywide geographical variation in the proportion diagnosed, identifies the geographical location of undiagnosed people living with HIV, and estimates how many undiagnosed individuals live in these areas. We show the utility of our approach by applying it to Lesotho, a mountainous, landlocked country in South Africa (figure A), which had diagnosed 81% of people living with HIV, provided 92% of these individuals with treatment, and attained viral suppression in 88% of treated individuals by 2016–17. 4 To implement the approach, two types of data are necessary: georeferenced data on diagnosis levels and temporally concurrent, highresolution, gridded demographic data. The necessary demographic data are publicly available from the WorldPop database, 5 and the necessary diagnosis data are available from the Population HIV Impact Assessment (PHIA) surveys; these surveys have been conducted in14 African countries. The purpose of the PHIA surveys is to estimate how close these countries are to achieving UNAIDS treatment targets. 6 PHIA1 surveys were conducted between 2015 and 2019; PHIA2 surveys have been ongoing since late 2019. The PHIAs are nationally representative crosssectional studies; the PHIA conducted in Lesotho is referred to as LePHIA. Each PHIA is based on a two-stage cluster sampling strategy. 7 Individuals were randomly sampled within each cluster and then geolocated to the cluster centroid. The clusters were then geographically displaced (ie, masked) to ensure anonymity. 7 The PHIAs collected detailed individual information on HIV testing, uptake of HIV services, and adherence to treatment. Participants answered questionnaires and provided biometric data, which were linked to their questionnaire. Blood samples were used to identify the HIV status of each individual, and (in people living with HIV) to quantitatively assess viral load and detect antiretroviral medications. People living with HIV were considered diagnosed if they were aware that they were infected or if antiretroviral medications were detected in their blood. To quantify countrywide geographical variation in the proportion diagnosed with HIV, we used data from LePHIA1 (collected in 2016 and 2017) to estimate the percentage of people living with HIV who had been diagnosed at each cluster site. We