PrEP Uptake and Adherence Among Young Black MSM: Neighborhood and Network Determinants

项目总结 该项目寻求使用实时地理空间方法来调查全球定位之间的关系 系统(GPS)定义的活动空间社区、社会和性网络以及艾滋病毒预暴露 预防(PrEP)在年轻黑人男性中的横向和纵向吸收和依从性 在芝加哥伊利诺伊州城市统计区(MSA)进行了两年多的与男性发生性行为(MSM)。我们 将在NIH资助的UConnect社区和网络队列计划中招募350名黑人MSM 研究，以解决研究的目标。资格要求包括：艾滋病毒血清阴性；自我报告否 限制平时的身体活动；未来两年没有计划搬到芝加哥IL MSA以外的地方；以及 愿意在两年内的九个时间点完成为期两周的GPS协议。参赛者将穿着 GPS设备遵循我们在之前的可行性研究项目中使用的协议，包括研究 在黑人MSM中。在这项纵向研究中，在完成最初为期两周的GPS方案三个月后， 在这项为期两年的研究中，参与者将每三个月额外携带GPS设备两周 期间--总共有九次。GPS活动、空间环境和社会/性网络基线数据 可能会随着时间的推移潜在地影响PrEP的结果。此外，多重GPS测量和社交/性网络 (在不同的时间点)可以更好地捕捉人们接触邻里因素的广度，以及 社交/性网络中的动态。这项拟议的研究将是全球定位系统对艾滋病毒差异的最大规模的研究 这为研究环境对艾滋病毒预防的影响提供了一个难得的机会。 拟议研究的结果将影响艾滋病毒预防干预活动。首先，它将通知 具体的邻里层面的政策干预。例如，社区加大了打击女同性恋的力度， 同性恋、双性恋和变性人仇恨犯罪率通过增加当地警方对高 犯罪地点可能是艾滋病毒预防干预措施，可以减少艾滋病毒健康差距。第二，从 GPS数据集，我们将知道黑色MSM的旅行模式，因此能够识别最佳 艾滋病毒预防干预的地理位置。这将推动文学的发展，因为这样 干预措施很少有地理针对性。第三，这项研究将有助于识别 适合在研究中招募黑人男男性接触者的地理位置，改进的场地方法- 基于抽样，在这个研究不足的人群中。第四，检查空间流动性的变化(即活动 空间)随时间变化将有助于了解特定空间的风险是变化还是保持不变 因为不同的社区会有不同的风险概况。不断变化的风险环境表明 这种预防需要极大的活力和流动性，以及快速的变化检测反馈循环。 最后，我们提出的动态网络分析将加深对社会和性别影响的理解 加强艾滋病毒预防行为网络，并将改进基于网络的艾滋病毒预防干预措施。

PROJECT SUMMARY This project seeks to use real-time geospatial methods to investigate relationships between Global Positioning System (GPS)-defined activity space neighborhoods, social and sexual networks, and HIV pre-exposure prophylaxis (PrEP) uptake and adherence cross-sectionally and longitudinally among young Black men who have sex with men (MSM) in the Chicago IL metropolitan statistical area (MSA) followed over two years. We will enroll 350 Black MSM in the proposed NIH-funded uConnect Neighborhoods and Networks Cohort Study to address the aims of the research. Eligibility requirements include: HIV-seronegative; self-report no restrictions to usual physical activity; no plans to move outside of Chicago IL MSA in the next two years; and willingness to complete a two-week GPS protocol at nine time-points over two years. Participants will wear the GPS device following protocols we have used in our previous feasibility research projects, including studies among Black MSM. In this longitudinal study, three months after completing the initial 2-week GPS protocol, participants will carry the GPS device for an additional 2-weeks every three-months over the two-year study period—for a total of nine times. GPS activity space environment and social/sexual networks data at baseline could potentially influence PrEP outcomes over time. Also, multiple GPS measures and social/sexual networks (at different time points) can better capture the breadth of people’s exposure to neighborhood-level factors and dynamics in social/sexual networks. The proposed study will be the largest GPS study of HIV disparities in any MSM population and presents a remarkable opportunity to study environmental influences on HIV prevention. Findings from the proposed research will impact HIV prevention intervention activities. First, it will inform specific neighborhood-level policy interventions. For example, increased community efforts to combat lesbian, gay, bisexual and transgender hate crime neighborhood rates through increased local police attention in high- crime locations may be an HIV prevention intervention that can reduce HIV health disparities. Second, from the GPS dataset we will know the travel patterns of Black MSM and therefore be able to identify optimal geographic locations for HIV prevention interventions. This will advance the literature given that such interventions are seldom geographically targeted. Third, this research will facilitate the identification of geographic locations suitable for recruiting Black MSM in research studies, an improved method of venue- based sampling, in this understudied population. Fourth, examining changes in spatial mobility (i.e. activity spaces) over time will be useful in knowing whether the risks of particular spaces changes or remain constant because different neighborhoods will have different risk profiles. Changing risk environments would suggest that prevention requires significant dynamism and fluidity, as well as rapid change-detection feedback loops. Finally, our dynamic network analysis we propose will deepen understanding of the effects of social and sexual networks on HIV prevention behaviors and will improve network-based HIV prevention interventions.