Individual, Network and Spatial Drivers of HIV and HCV among PWID in India

 描述：注射毒品（PWID）的人承担着艾滋病毒和丙型肝炎病毒（HCV）的高负担，并且沿着艾滋病毒护理连续体的情况更糟。个人，网络和空间因素之间的相互作用对艾滋病毒/丙型肝炎病毒的风险，特别是在资源有限的环境中，一直研究不足。此外，大多数网络评估都是跨部门的，并且重点关注以自我为中心的网络。随着时间的推移，网络的动态，自我中心网络与更广泛的社会计量或空间网络的关系，以及这些更大的网络对疾病传播和寻求健康行为的影响，人们了解得较少。印度是全球阿片类药物使用者人数最多的国家;艾滋病毒和丙型肝炎病毒的流行率分别为20%和50%。我们目前正在实施一项随机分组试验，以评估综合护理中心对艾滋病毒护理连续性结果的有效性。在本试验的评估（2016年7月至12月）中，我们将在12个城市使用受访者驱动抽样（RDS）收集样本-这将作为本研究的起点。这些认可机构包括：目标1：评估空间、网络和个人层面因素对印度三个城市艾滋病毒/艾滋病感染者中艾滋病毒和HCV发病率的影响，选择这些城市以反映不同的艾滋病毒/艾滋病感染者流行病; Subaim 1a：使用系统发育数据描述吸毒网络中艾滋病毒/HCV传播的特征;目标2：评估吸毒网络中与艾滋病毒护理连续体相关的行为变化的社会扩散;目标3：通过将详细的网络数据覆盖在RDS招募过程中，开发在PWID人群中应用RDS的改进方法; Subaim 3a：描述影响PWID如何向其网络成员分发优惠券的因素以及该过程对RDS得出的估计值的影响; Subaim 3b：制定改进的RDS招募策略，以克服Subaim 3a; Subaim 3c中发现的偏倚：确定RDS网络和遗传学定义的聚类之间的重叠，以告知RDS用于干预交付和人群推导的使用-目标4：为今后的研究工作建立一个平台。我们将在印度3个艾滋病毒/毒品使用流行情况不同的城市--丘拉昌布尔、阿姆利则和坎普尔建立一个多中心动态队列。我们将描述来自RDS评估的前350名参与者的社交网络，并招募在过去6个月内注射过这些参与者的人。我们将反复描述和招募新招募的合格网络成员，直到没有发现额外的新网络成员（每个研究中心约750个;总共2250个）。生物识别数据、全球定位系统坐标和网络软件将有助于跟踪和查明跨网络联系。将每半年对参与者进行一次跟踪，并根据确定的情况招募新的网络成员。我们的研究在跟踪时间网络动态，使用新方法来表征社会计量和空间网络，使用系统发育数据表征网络对传播的影响以及PWID网络中与HIV相关的健康寻求行为的社会扩散方面具有创新性。

 DESCRIPTION: People who inject drugs (PWID) bear a high burden of HIV and hepatitis C virus (HCV) and fare worse along the HIV care continuum. The interplay between individual, network and spatial factors on HIV/HCV risk, particularly in resource-limited settings, has been understudied. Further, most network assessments have been cross-sectional and have focused on egocentric networks. Less is understood about the dynamics of networks over time, relationship of egocentric networks to the broader sociometric or spatial networks, and the impact of these larger networks on disease transmission and health seeking behaviors. India is home to the largest number of opiate users globally; HIV and HCV prevalence is 20% and 50%, respectively. We are currently implementing a cluster-randomized trial to assess the effectiveness of integrated care centers on HIV care continuum outcomes among PWID. In the evaluation of this trial (July - December 2016), we will accrue a sample using respondent driven sampling (RDS) in 12 cities - this will serve as the starting point for this study. The specific ais are: Aim 1: To assess the impact of spatial-, network- and individual-level factors on HIV and HCV incidence among PWID in three Indian cities, selected to reflect diverse HIV/PWID epidemics; Subaim 1a: Use phylogenetic data to characterize HIV/HCV transmission in drug using networks; Aim 2: To assess the social diffusion of behavior change in relation to the HIV care continuum within drug using networks; Aim 3: To develop improved methodology for the application of RDS in PWID populations by overlaying detailed network data on an RDS recruitment process; Subaim 3a: To characterize factors that influence how PWID distribute coupons to members of their networks and the impact of this process on RDS- derived estimates; Subaim 3b: To develop improved RDS recruitment strategies to overcome biases identified in Subaim 3a; Subaim 3c: To determine overlap between the RDS network and phylogenetically-defined clusters to inform the use of RDS for intervention delivery and derivation of population-level estimates; and Aim 4: To establish a platform for future research studies. We will establish a multi-center dynamic cohort across 3 cities with diverse HIV/drug use epidemics in India - Churachandpur, Amritsar and Kanpur. We will characterize the social network of the first 350 participants from the evaluation RDS and recruit those who have injected with these participants in the prior 6 months. We will characterize and recruit eligible network members of new recruits iteratively until no additional new network members are identified (~750 per site; 2250 total). Biometric data, GPS coordinates and network software will facilitate tracking and identifying cross-network linkages. Participants will be followed semi-annually and new network members recruited as identified. Our study is innovative in its ability to track temporal network dynamics, use of novel methodology to characterize sociometric and spatial networks, characterization of network impact on transmission using phylogenetic data, and the social diffusion of health-seeking behaviors related to HIV within PWID networks.