Activity spaces for HIV risk and prevention among diverse men who have sex with men in Los Angeles

摘要 结束美国艾滋病毒流行的关键战略之一是增加对 地理热点，或疾病负担较高的地区。然而，一些关键挑战限制了 热点图，为有效的艾滋病毒干预提供信息。首先，热点映射通常使用住宅地址 意外感染的个人。然而，对许多人来说，潜在的危险性行为和吸毒行为 不要在家里发生。识别风险发生的地方，而不是个人 从事风险生活，将有助于确定目标并增加对以地方为基础的干预措施的暴露。第二，个人 行为往往受到更大的社会生态因素的制约或支配，这些因素可以共同作用来 制造或维持健康差距。针对风险热点量身定做的干预措施，以改善艾滋病毒护理级联 需要对热点的更广泛的社会生态背景作出反应。第三，一个隐含的假设 关于对热点进行干预的优先顺序是，减少热点发病率的努力将间接减少 其他地方的发病率也是如此，因为感染可能从高发地区传播到邻近较低的地区 流行地区。关于热点和性网络之间潜在的地理和性网络连接的信息 其他地方可以告知艾滋病毒干预工作风险热点的优先顺序。 我们将展示创新的方法，在城市、非白人中识别和优先处理艾滋病毒风险热点 男男性行为者(MSM)是美国艾滋病毒感染风险特别高的人群。我们会 利用和补充现有的关于非白人MSM的纵向数据，包括感染艾滋病毒和未感染的数据，来自 在洛杉矶正在进行的mStudy队列，以实现我们的目标。我们将首先改编现有的基于Web的 艾滋病毒风险和预防的活动空间调查，以纳入网络的地理特征， 居住流动性和吸毒地点。然后，我们将使用认知访谈来验证调查 工具，并使用更新的调查从250名男男性接触者中收集数据。第二，我们将识别和描述 使用个人活动空间数据，洛杉矶县内的艾滋病毒传播和感染风险热点 性行为风险与吸毒地点、热点社区特征及社会人口学 热点地区个体参与风险的特征和行为。第三，我们将估计 热点到其他位置(例如，其他热点、住宅位置和预防位置)的连通性， 以便确定在时间和空间上最大限度地提高干预效果的优先顺序。 这项工作将从两个方面提高艾滋病毒预防、护理和治疗战略的有效性。首先，它 将根据潜在的连接性对热点进行排序，从而指导决策制定 其他地方，从而最大限度地扩大干预的范围。其次，它将告知哪种组合 通过描述热点的背景和组成，干预将是最成功的。

Abstract One of the key strategies to ending the HIV epidemic in the United States is to increase investments in geographic hotspots, or areas of elevated disease burden. However, a few key challenges limit the ability for hotspot mapping to inform effective HIV interventions. First, hotspot mapping typically uses residential address of an individual with an incident infection. Yet for many individuals, potential risky sex and drug-use behaviors do not occur at home. Identifying the places in which risk occurs, as opposed to where an individual who engages in risk lives, will help target and increase exposure to place-based interventions. Second, individual behavior is often constrained or dictated by larger socio-ecological factors, and these can work together to create or maintain health disparities. Interventions tailored to risk hotspots to improve the HIV care cascade need to be responsive to the broader socio-ecological context of the hotspot. Third, an implicit assumption about prioritizing hotspots for interventions is that efforts to reduce incidence in hotspots will indirectly reduce incidence elsewhere as well, as infections likely spread from high incidence areas to neighboring lower prevalence areas. Information on potential geographic and sexual network connectivity between hotspots and other places can inform prioritization of risk hotspots for HIV interventions. We will demonstrate innovative methods to identify and prioritize HIV risk hotspots among urban, non-white men who have sex with men (MSM), populations at especially high-risk for HIV in the United States. We will leverage and supplement existing longitudinal data on non-White MSM, both HIV-infected and uninfected, from the ongoing mStudy cohort in Los Angeles, to achieve our goals. We will first adapt an existing web-based activity space survey of HIV risk and prevention to incorporate geographic characteristics of networks, residential mobility, and locations of drug use. Then we will use cognitive interviews to validate the survey instrument, and collect data from 250 MSM using the updated survey. Second, we will identify and describe HIV transmission and acquisition risk hotspots within Los Angeles County, using individual activity space data on sexual risk and drug use locations, neighborhood characteristics of the hotspots, and sociodemographic characteristics and behaviors of individuals engaging in risk in the hotspots. Third, we will estimate connectivity of hotspots to other locations (e.g., other hotspots, residential locations, and prevention locations), in order to identify which hotspot to prioritize for maximizing intervention effectiveness over time and space. This work will improve the effectiveness of HIV prevention, care, and treatment strategies in two ways. First, it will guide decision making as to which hotspot to prioritize, by ranking them in terms of potential connectivity to other places, and thus maximizing the reach of the intervention. Second, it will inform which combination of interventions will be most successful, by characterizing the context and composition of the hotspot.