Test and Linkage to Care (TLC_IDU) Kenya

描述（由申请人提供）：在撒哈拉以南非洲，艾滋病毒感染越来越多地发生在注射毒品使用者（IDUs）中，这是一个最危险的人群（MARP）。该区域没有为注射吸毒者提供循证服务，如针头和注射器交换方案、阿片类药物替代疗法和注射吸毒者专用抗逆转录病毒疗法坚持支持。肯尼亚正在对注射吸毒者的人数进行估计，并准备启动有史以来的第一个国家战略计划。我们的肯尼亚政策领导人、成瘾/行为科学家和建模者团队将利用肯尼亚新的MARP/NSP平台寻找注射吸毒者，提供快速艾滋病毒检测、护理点CD 4计数和与抗逆转录病毒疗法的联系，并评估内罗毕和沿海蒙巴萨的社区病毒载量，肯尼亚大多数注射吸毒者居住在那里。目的1：评价寻求测试治疗保留-“测试和联系，以照顾注射吸毒者”（TLC-IDU肯尼亚）-使用阶梯楔形群随机设计。集群将是计划的n=20个MARP服务站点和n=5个NSP。我们将启动应答者驱动抽样（RDS），以接触内罗毕和蒙巴萨的注射吸毒者，确定基线HIV-1流行率，然后随着服务站点的推出，收集七波研究数据，包括PDA上的行为数据。小组将进行快速艾滋病毒检测，并转介成瘾/心理健康和OST。艾滋病毒阳性者将接受阳性预防（PwP）咨询和护理点CD 4计数。CD 4 <350/<L的患者将被指派一名同行病例管理员，在参与研究的HIV诊所将患者与ART联系起来，支持ART和PwP依从性和护理保留。同侪病例管理者和受试者都将收到小额有条件现金转移，以确保受试者坚持接受艾滋病毒护理访视。主要研究结果将包括成功连接到护理的时间、ART的时间以及开始TLC-IDU前后的社区病毒载量。将通过从n=25个研究中心的每个研究中心随机选择的n=10份HIV阳性样本中采集标本，确定“社区病毒载量”。随着时间的推移，该采样将分八波进行，以记录感染性（中位病毒载量）的变化。每个时间步每个研究中心有7个单独的病毒载量（n=1400），当使用线性混合效应分析比较干预前后时，我们将有很好的把握度检测log 10病毒载量变化0.23和风险比约1.5。目标二：进行数学建模，以估计注射吸毒者和性网络中的社区病毒载量，并评估TLC-IDU干预对Ro、避免的感染数量和质量调整预期寿命的潜在人群水平影响。目标3：从国家支付者的角度评估TLC-IDU模式的增量成本效益比。这项研究将提供世界上第一批关于在撒哈拉以南非洲对注射吸毒者实施“寻找、检测、治疗和保留”模式的数据。它将展示结构、生物医学和行为干预相结合可以减少传染性的程度。与肯尼亚国家艾滋病毒方案的伙伴关系将使从这项研究中吸取的经验教训能够为其他国家提供信息，这些国家正在考虑如何最好地解决这个艾滋病毒高负担地区日益增长的注射吸毒对艾滋病毒流行的贡献。

DESCRIPTION (provided by applicant): HIV infections in sub-Saharan Africa increasingly occur among injecting drug users (IDUs), a most-at-risk population (MARP). Evidence-based services for IDUs such as needle and syringe exchange programs (NSPs), opioid substitution therapy (OST), and IDU-specific antiretroviral therapy (ART) adherence support have been non-existent in this region. Kenya is conducting size estimations of IDUs and is preparing to launch first-ever NSPs. Our team of Kenyan policy leaders, addiction/behavioral scientists and modelers will leverage Kenya's new MARPs/NSP platform to seek out IDUs, deliver rapid HIV testing, point of care CD4 count and link to ART, and evaluate community viral load in Nairobi and coastal Mombasa, where most IDUs in Kenya reside. Aim 1: Evaluate seek test treat retain - 'Testing & Linkage to Care for IDUs' (TLC-IDU Kenya) - using a stepped wedge cluster-randomized design. Clusters will be the planned n=20 MARP service sites and n=5 NSPs. We will initiate respondent-driven sampling (RDS) to reach IDUs in Nairobi and Mombasa for baseline HIV-1 prevalence determination, and then collect seven waves of study data as service sites roll out, including behavioral data on PDAs. Teams will do rapid HIV testing and refer for addiction/mental health and OST. HIV-positives will receive prevention with positives (PwP) counseling and point of care CD4 counts. Those with CD4 <350/<L will be assigned a peer case manager to link the person to ART at study-participating HIV clinics, support ART and PwP adherence and care retention. Both peer case managers and subjects will receive small conditional cash transfers for subject's adherence to HIV care visits. Primary study outcomes will include time to successful linkage to care, time to ART, and community viral load before and after the TLC-IDU initiation. 'Community viral load' will be ascertained by collecting specimens from n=10 randomly-selected HIV-positives at each of n=25 sites. This sampling will be done in eight waves over time, to document changes in infectivity (median viral load). With seven individual viral loads per site per time step (n=1400) we will have good power to detect log10 viral load changes of 0.23 and hazard ratios of ~1.5 when comparing pre- and post-intervention period using linear mixed effects analysis. Aim 2: Conduct mathematical modeling to estimate community viral load in IDU injecting and sexual networks, and to assess potential population-level impact of the TLC-IDU intervention on Ro, numbers of infections averted, and quality-adjusted life expectancy. Aim 3: Assess the incremental cost-effectiveness ratio of the TLC-IDU model, using a national payer perspective. This study will provide among the world's first data regarding implementation of the seek, test, treat and retain paradigm with IDUs in sub-Saharan Africa. It will demonstrate the degree to which a combination of structural, biomedical and behavioral interventions can reduce infectivity. Partnership with Kenya's national HIV program will allow lessons learned from this study to inform other countries considering how best to address the growing IDU contribution to the HIV epidemic in this high-HIV-burden region.