艾滋病毒检测方案一直在努力覆盖面临艾滋病毒风险的最边缘化人群。诸如受访者驱动的抽样(RDS)和基于同伴的主动病例发现(ACF)之类的社交网络方法可能有效地克服了到达这些人群的障碍。我们比较了客户的特点,比例检测HIV阳性(产量),以及通过两种RDS策略和ACF方法在塔吉克斯坦注射吸毒者中发现艾滋病毒病例(PWID)发现的新病例数量。
分析了在塔吉克斯坦HIV旗舰项目下招募的成人PWID的常规计划数据,以比较三种方法的客户人口统计学和临床特征。我们还比较了以前未经测试的客户数量,新发现的艾滋病毒病例数量,以及案件调查策略的收益率,并使用固定效应逻辑回归评估新HIV诊断的预测因子。
从2016年10月24日至2017年6月30日,旗舰对10,300名PWID进行了HIV检测,包括具有不受限制波浪的RDS下的2143(RDS1,收益率:1.5%),受限RDS(RDS2,收益率:2.6%)下的3517,在ACF下和4640(收益率:1.5%)。在ACF下招募的客户年龄相似(35.8vs.36.8)和性别(91%vs.90%男性)通过RDS招募的人,尽管ACF客户更有可能报告是首次测试人员(85.1%与68.3%,p<0.001)。在控制了年龄之后,性别,以前的测试历史和对站点级别聚类的解释,我们发现,根据RDS1(aOR:1.74,95%CI:1.04~2.90)和RDS2(aOR:1.54,95%CI:1.11~2.15)进行检测的客户与通过ACF招募的客户相比,HIV新检测阳性的几率更高.我们没有发现从RDS1招募的人与RDS2招募的人之间新发HIV感染的几率存在显着差异(aOR:1.12,95%CI:0.67至1.86)。
基于RDS的干预措施导致更高的产量和总体病例发现,特别是在招聘受到限制的情况下。然而,ACF确定了较高比例的首次测试人员。为了在塔吉克斯坦发现至少90%的PWID感染艾滋病毒,可能有必要同时实施多种病例查找方法,以最大限度地提高测试覆盖率。
HIV testing programmes have struggled to reach the most marginalized populations at risk for HIV. Social network methods such as respondent-driven sampling (RDS) and peer-based active
case-finding (ACF) may be effective in overcoming barriers to reaching these populations. We compared the client characteristics, proportion testing HIV positive (yield), and number of new cases found through two RDS strategies and an ACF approach to HIV
case-finding among people who inject drugs (PWID) in Tajikistan.
Routine programme data from adult PWID recruited to testing under the HIV Flagship Project in Tajikistan were analysed to compare client demographic and clinical characteristics across the three approaches. We also compared the number of previously untested clients, the number of new HIV cases found, and the yield across the
case-finding strategies, and evaluated predictors of new HIV diagnosis using fixed-effects logistic regression.
From 24 October 2016 to 30 June 2017, Flagship tested 10,300 PWID for HIV, including 2143 under RDS with unrestricted waves (RDS1, yield: 1.5%), 3517 under restricted RDS (RDS2, yield: 2.6%), and 4640 under ACF (yield: 1.5%). Clients recruited under ACF were similar in age (35.8 vs. 36.8) and gender (91% vs. 90% male) to those recruited through RDS, though ACF clients were more likely to report being a first-time tester (85.1% vs. 68.3%, p < 0.001). After controlling for age, sex, previous testing history and accounting for clustering at the site level, we found that clients tested under both RDS1 (aOR: 1.74, 95% CI: 1.04 to 2.90) and RDS2 (aOR: 1.54, 95% CI: 1.11 to 2.15) had higher odds of testing newly positive for HIV relative to clients recruited through ACF. We did not find significant differences in the odds of new HIV infection between those recruited from RDS1 versus RDS2 (aOR: 1.12, 95% CI: 0.67 to 1.86).
RDS-based interventions resulted in higher yields and overall
case-finding, especially when recruitment was restricted. However, ACF identified a higher proportion of first-time testers. To find at least 90% of PWID living with HIV in Tajikistan, it may be necessary to implement multiple
case-finding approaches concurrently to maximize testing coverage.