Assessing the impact of an intervention to prevent violence and HIV in Uganda

乌干达拉凯的特点是艾滋病毒流行成熟，亲密伴侣暴力(IPV)发生率高。2005年，成人艾滋病毒感染率为16%(女性)和12%(男性)，发病率为1.5/100人年(PY)；而在过去一年中，分别有20%和14.5%的女性报告了身体或性感染。这是一个重大的公共卫生问题，因为经历过IPV的妇女感染艾滋病毒的风险增加，感染艾滋病毒的妇女感染IPV的风险增加。虽然选定的干预措施独立地减少了艾滋病毒和IPV，但没有一种单一的方法成功地减少了这两种结果。这项拟议研究的目的是评估安全家园和尊重每个人(SHARE)项目的影响，该项目是由Rakai健康科学计划(RHSP)进行的艾滋病毒/IPV综合干预措施。分享的设计以行为改变的跨理论模式为基础，包括与社区志愿者合作、卫生动员和教育、能力建设活动、宣传、媒体和特别活动。采用整群随机试验设计，通过母公司研究Rakai社区队列研究(RCCS)收集数据，该研究每12-18个月收集一次调查和生物学数据，所有年龄在15-49岁的人都同意。在基线时，47个活跃的农村合作与合作社区被分成11个组，其中4个被分配到试验的干预组，7个被分配到控制组。干预地区获得了分享和RHSP服务，包括艾滋病毒检测、提供抗逆转录病毒治疗和抗逆转录病毒治疗前护理、一般医疗保健、预防艾滋病毒母婴传播、计划生育、健康教育和社区动员。控制区没有暴露于SHARE，但暴露于RHSP服务。通过RCCS调查和干预前(2005年2月至2006年6月)和干预后2次随访(2006年8月至2009年11月)进行影响评估。基线时共有14,119名参与者(干预社区3,316名，对照社区10,803名)参加。这项拟议的研究有三个目标。目的1：与对照社区相比，评估干预措施对过去12个月期间身体和/或性传播疾病流行率的影响。调整后的流行风险比(PRR)将使用对数二项回归或修正的泊松回归和随机影响模型进行估计，以考虑组内相关性。目的2：与对照社区比较，评估干预对HIV发病率的影响。将遵循意向治疗的方法，使用对数链接和泊松分布来估计每100年感染艾滋病毒的发生率比率(IRR)，使用随机效应模型来考虑组内相关性和按组调整。目的3：与对照社区比较，评估干预对性危险行为(过去一年的非婚伙伴关系、过去6个月的避孕套使用和性行为前饮酒)的影响。PRR将使用对数二项式回归或修正的泊松回归和随机效应模型来估计，以考虑集群内的相关性。

Rakai, Uganda is characterized by a mature HIV epidemic and high rates of intimate partner violence (IPV). In 2005, adult HIV prevalence was 16% (women) and 12% (men) and incidence was 1.5/100 person-years (PY); while 20% and 14.5% of women reported physical or sexual IPV (respectively) during the past year. This represents a significant public health concern because women who experience IPV are at increased risk for HIV acquisition and HIV-infected women are at increased risk for IPV. Although select interventions have independently reduced HIV and IPV, no one-dimensional approach has successfully decreased both outcomes. The objective of the proposed research is to assess the impact of the Safe Homes And Respect for Everyone (SHARE) Project, a combination HIV/IPV intervention conducted by Rakai Health Sciences Program (RHSP). The SHARE design was based on the Transtheoretical Model of behavior change and included work with community volunteers, health mobilization and education, capacity building activities, advocacy, media and special events. A cluster randomized trial design was used and data were collected via the parent study, the Rakai Community Cohort Study (RCCS), which collects survey and biological data every 12-18 months with all consenting people aged 15-49. At baseline there were 47 active RCCS communities grouped into 11 clusters, 4 of which were assigned to the intervention arm and 7 to the control arm of the trial. Intervention areas were exposed to SHARE and RHSP services including HIV testing, provision of ART and pre-ART care, general medical care, prevention of mother-to-child HIV transmission, family planning, health education and community mobilization. Control areas were not exposed to SHARE but were exposed to RHSP services. Impact assessment was done through RCCS surveys and HIV serology done pre-intervention (Feb 2005-June 2006) and at 2 post-intervention follow-ups (Aug 2006-Nov 2009). A total of 14,119 participants (3,316 in intervention communities and 10,803 in control communities) were enrolled at baseline. The proposed research has 3 aims. Aim 1: To assess the impact of the intervention on the period prevalence of physical and/or sexual IPV in the past 12 months compared to the control communities. Adjusted prevalence risk ratios (PRR) will be estimated using log-binomial or modified Poisson regression with random effects models to account for within-cluster correlation. Aim 2: To assess the impact of the intervention on HIV incidence compared with control communities. An intention-to-treat approach will be followed using a log link and Poisson distribution to estimate the incidence rate ratios (IRR) of HIV acquisition per 100 PY, using random effects models to account for intra-cluster correlation and adjusting by cluster. Aim 3: To assess the impact of the intervention on sexual risk behaviors (non-marital partnerships in the past year, condom use over the past 6 months and use of alcohol before sex) compared to the control communities. PRRs will be estimated using log-binomial or modified Poisson regression with random effects models to account for correlation within clusters.