Modeling interactions between HIV interventions in key populations in India

模拟印度重点人群艾滋病毒干预措施之间的相互作用

• 批准号: 8846213
• 负责人: Derek A Cummings
• 金额: $ 24.3万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-07-06 至 2016-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8846213
• 关键词: AIDS prevention; Africa South of the Sahara; Caring; Cities; Cluster randomized trial; Cost Effectiveness Analysis; Counseling; Country; Data; Data Analyses; Drug usage; Education; Epidemic; Evaluation; Funding; Future; Government; Graph; HIV; Heterosexuals; Incidence; Income; India; Individual; Intervention; Lead; Left; Methods; Modeling; Needle-Exchange Programs; Opioid Rotation; Parents; Pharmaceutical Preparations; Policies; Population; Prevalence; Prevention; Prevention strategy; Prevention trial; Preventive Intervention; Respondent; Sampling; Services; Sexually Transmitted Diseases; Site; Testing; Translational Research; United States National Institutes of Health; Validation; Work; World Health Organization; antiretroviral therapy; base; community intervention; condoms; cost effectiveness; design; implementation science; improved; model building; network models; novel; programs; public health relevance; response; scale up; simulation; success; transmission process; tuberculosis treatment

 DESCRIPTION (provided by applicant): This application proposes to use multiple modeling frameworks to examine interaction between HIV prevention interventions delivered in a combination package among a hard to reach population, people who inject drugs (PWID), in a low-and-middle income country setting (LMIC), India. Combination prevention has been recognized as the key to eradication of HIV. Critical to the determination of success of such programs will be the extent to which interventions act synergistically. Transmission models, which have been important drivers of policy for HIV prevention and treatment interventions, can help to disentangle multiple dynamic effects of combination interventions. Moreover, models can be parameterized with detailed representations of networks of interaction. However, thus far, the majority of combination prevention efforts and modeling efforts have been focused on heterosexual-driven HIV epidemics. We will leverage an NIH R01 funded cluster-randomized trial of integrated care centers to control HIV in PWID (DA032059, The NCA Study; PI: Mehta, Lucas). The intervention is a combination of the nine interventions currently recommended for PWID by the World Health Organization, including HIV counseling & testing, antiretroviral therapy, opioid substitution, needle exchange, treatment of sexually transmitted infections, treatment of tuberculosis, education and condoms, delivered in an integrated care center. A baseline sample of 14,450 was accrued using respondent-driven sampling (RDS) across 15 cities in Northeastern, Northern, and Central India. Six cites have been scaled up to receive the intervention and six will receive the control condition (all services available in distinct centers. An evaluation sample of 12,000 will be collected two years after implementation of the intervention. The parent study is underway and no additional approvals will be required from the Indian government for the proposed study. Our aims are to: 1) Explain differences in prevalence and incidence of HIV in multiple populations of PWID in India using mechanistic transmission models; and 2) Estimate the impact of multiple interventions and their interaction using mechanistic transmission models. For Aim 1, we will 1) use novel statistical inference methods to infer multiple simulated networks that are consistent with the observed data from the NCA study baseline sample accrued using RDS (n=14,450); 2) build transmission models of HIV using simulated networks of PWID estimated above; and 3) perform model validation of best fitting models using repeated leave-out one site (of 15) methods. For Aim 2, we will 1) use models developed in Aim 1 to estimate the impact of combination interventions currently being implemented in the NCA study as well as other novel interventions (e.g., PrEP); and 2) validate simulated marginal benefits of interventions. Our modeling framework can be extended to incorporate interventions not being delivered as part of the package in the NCA study (e.g., PrEP), can be extended to other hard to reach populations in India as well as PWID in other LMICs and finally as the basis for future cost-effectiveness analyses for this and other settings.

 描述（由申请人提供）：本申请建议使用多个建模框架来检查在印度的中低收入国家（LMIC）中，在难以接触的人群（注射毒品者（PWID））中，以组合方案提供的艾滋病毒预防干预措施之间的相互作用。综合预防被认为是根除艾滋病毒的关键。决定这些方案成功与否的关键是干预措施发挥协同作用的程度。传播模式一直是艾滋病毒预防和治疗干预措施政策的重要驱动力，有助于理清综合干预措施的多重动态影响。此外，模型可以通过交互网络的详细表示来参数化。然而，到目前为止，大多数联合预防工作和建模工作都集中在异性恋驱动的艾滋病毒流行病上。我们将利用NIH R 01资助的综合护理中心的随机分组试验来控制PWID中的HIV（DA 032059，NCA研究; PI：Mehta，Lucas）。该干预措施是世界卫生组织目前推荐的针对PWID的九项干预措施的组合，包括艾滋病毒咨询和检测，抗逆转录病毒治疗，阿片类药物替代，针头交换，性传播感染治疗，结核病治疗，教育和避孕套，在综合护理中心提供。在印度东北部、北方和中部的15个城市，使用应答者驱动抽样（RDS）累积了14，450个基线样本。六个城市已扩大规模，接受干预，六个将接受控制条件（所有服务可在不同的中心。在实施干预措施两年后，将收集12 000个评价样本。母研究正在进行中，拟议研究无需获得印度政府的额外批准。我们的目标是：1）使用机械传播模型解释印度多个PWID人群中艾滋病毒流行率和发病率的差异; 2）使用机械传播模型估计多种干预措施及其相互作用的影响。对于目标1，我们将1）使用新的统计推断方法推断多个模拟网络，这些网络与使用RDS（n= 14，450）获得的NCA研究基线样本的观察数据一致; 2）使用上述估计的PWID模拟网络构建HIV传播模型; 3）使用重复遗漏一个站点（共15个）方法对最佳拟合模型进行模型验证。对于目标2，我们将1）使用目标1中开发的模型来估计目前在NCA研究中实施的联合干预措施以及其他新型干预措施（例如，PrEP）; 2）验证干预措施的模拟边际效益。我们的建模框架可以扩展，以纳入未作为NCA研究中一揽子计划的一部分提供的干预措施（例如，PrEP），可以扩展到印度其他难以接触的人群以及其他中低收入国家的PWID，并最终作为未来这种和其他环境的成本效益分析的基础。