Impact of Social Cohesion and Social Capital in PrEP Uptake and Adherence Among Transwomen of Color

项目摘要 该项目旨在使用实时地理空间方法来调查社会凝聚力之间的关系， 全球定位系统（GPS）定义的活动空间社区和社会资本 与艾滋病毒暴露前预防（PrEP）的吸收和跨部门坚持有关的网络， 在纽约市大都市统计数据中， MSA（MSA）是一个为期两年的项目。我们将在拟议的N2研究中招募250名TWOC：变性人 妇女的邻里和网络队列研究，以解决研究的目的。资格 要求包括：确定为变性妇女（出生时被指定为男性的个人） 认同为女性、女性、跨性别女性、跨性别女性、男性对女性或其他不同的跨性别女性的人 有色人种; HIV血清反应阴性;年龄在18 - 55岁之间;居住在纽约 城市MSA;自我报告没有计划在未来两年内搬离纽约市大都市区; 自我报告对日常体力活动没有限制;自我报告愿意携带小型GPS设备 在两年的时间里，在五个点上持续两周。参加者将佩戴GPS设备， 我们以前的可行性研究项目中使用的协议，包括TW之间的研究。在这一纵向 在完成最初的2周GPS方案后6个月，参与者将携带GPS设备进行为期6周的研究。 在两年的研究期间，每六个月增加两周，总共五次。多个GPS 社交网络的度量和多个度量（在不同时间点）可以更好地捕捉 人们在社交网络中接触到的邻里层面的因素和动态。此外，GPS活动空间 基线的环境和社交网络数据可能会随着时间的推移影响PrEP结果， 提供了清晰的时间排序和考虑潜在时滞的能力。拟议的研究将 全球定位系统对任何变性人群中艾滋病毒差异的最大研究， 研究环境对艾滋病的影响。拟议研究的结果将影响艾滋病毒预防 干预活动。首先，该项目将为具体的社区一级政策干预提供信息。为 例如，通过增加社区的社会凝聚力来增加社区的努力可能是一种艾滋病毒， 预防干预可以减少艾滋病毒健康差距。其次，从GPS数据集，我们将知道 TW的旅行模式，因此能够确定预防艾滋病毒的最佳地理位置 干预措施。鉴于此类干预措施很少有地理目标，这将推动文献的发展。 第三，研究空间流动性（即活动空间）随时间的变化将有助于了解 特定空间的风险变化或保持不变，因为不同的社区将有不同的 风险概况。最后，我们提出的动态网络分析将加深对 社交网络的艾滋病毒预防行为，并将改善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 social cohesion and social capital within Global Positioning System (GPS)-defined activity space neighborhoods and social networks in relation to HIV pre-exposure prophylaxis (PrEP) uptake and adherence cross-sectionally and longitudinally among transgender women (TW) of color (TWOC) in the New York City metropolitan statistical area (MSA) followed over two years. We will recruit 250 TWOC in the proposed The N2 Study: Transgender Women's Neighborhood and Networks Cohort Study to address the aims of the research. Eligibility requirements include: identifying as a transgender woman (individuals who were assigned a male sex at birth who identify as women, female, trans women, trans female, male-to-female or another diverse trans feminine gender identity on the spectrum) of color; HIV-seronegative; being 18 to 55 years old; residing in the New York City MSA; self-report no plans to move outside of the New York City metropolitan area in the next two years; self-reporting no restrictions to usual physical activity; and self-report willingness to carry a small GPS device for two-weeks at five points over the course of two years. Participants will wear the GPS device following protocols used in our previous feasibility research projects, including studies among TW. In this longitudinal study, six months after completing the initial 2-week GPS protocol, participants will carry the GPS device for an additional 2-weeks every six-months over the two-year study period—for a total of five times. Multiple GPS measures and multiple measures of social networks (at different time points) can better capture the breadth of people's exposure to neighborhood-level factors and dynamics in social networks. Also, GPS activity space environment and social networks data at baseline could potentially influence PrEP outcomes over time, providing a clear temporal ordering and an ability to consider potential time-lags. The proposed study will be the largest GPS study of HIV disparities in any transgender population and presents a remarkable opportunity to study environmental influences on HIV. Findings from the proposed research will impact HIV prevention intervention activities. First, the project will inform specific neighborhood-level policy interventions. For example, increased community efforts through increased social cohesion in neighborhoods may be an HIV prevention intervention that can reduce HIV health disparities. Second, from the GPS dataset we will know the travel patterns of TW 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, examining changes in spatial mobility (i.e. activity spaces) over time will be useful in knowing whether the risks of particular spaces change or remain constant because different neighborhoods will have different risk profiles. Finally, our dynamic network analysis we propose will deepen understanding of the effects of social networks on HIV prevention behaviors and will improve network-based HIV prevention interventions.