Using Sexual Network Transmission Models to Explain HIV Disparities Between Black

使用性网络传播模型来解释黑人之间的艾滋病毒差异

• 批准号: 8601779
• 负责人: STEVEN M. GOODREAU
• 金额: $ 23.79万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-08-15 至 2015-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8601779
• 关键词: Accounting; Address; Age; Anus; Area; Behavioral; Characteristics; Code; Communities; Data; Data Analyses; Epidemic; Evaluation; Expert Opinion; Future; Graph; HIV; Incidence; Individual; Infection; Measures; Methods; Modeling; Participant; Pattern; Population; Prevalence; Preventive Intervention; Process; Property; Race; Reporting; Research Personnel; Risk; Role; Sex Behavior; Sexual Partners; Simulate; Source; Structure; Testing; Triad Acrylic Resin; United States; Work; base; innovation; mathematical model; member; men; men who have sex with men; metropolitan; models and simulation; network models; public health relevance; racial and ethnic disparities; racial difference; sex; theories; tool; transmission process

DESCRIPTION (provided by applicant): In the United States, disparities in HIV between black and white men who have sex with men (MSM) are large and unexplained. Individual behavioral reasons for these disparities have been generally dismissed as possible explanations. Network explanations have proven useful in understanding persistent disparities in STI burdens in other populations, and have been hypothesized to explain racial/ethnic disparities in US MSM. However, these hypotheses have not been tested using modeling approaches for two reasons. First, there have historically been inadequate data to parameterize models with respect to critical network characteristics, such as concurrency, transitivity, and assortative mixing by key characteristics. Second, model structures have not been developed that account for the unique aspects of MSM sexual networks. We propose to develop this understanding by analyzing new data on MSM sexual networks from multiple studies conducted by the investigators in Atlanta, a metropolitan area with large populations of both black and white MSM and significant racial disparities in HIV. We will recall participants in current and recent studies to collect additional data as necessary. Using these new network parameters, we will extend an existing stochastic simulation model of HIV transmission in MSM to reflect these network attributes. This approach will use STERGMs (separable temporal exponential random graph models), which can handle dynamic network data in the form of cross-sectional network structure combined with information on relational duration or dissolution patterns. We will use the expanded, newly parameterized model for two purposes. First, we will use the model to attempt to describe the role of network parameters in black/white disparities in HIV incidence among US MSM. Second, we will use the model to test which modifiable network parameters might have the most potential in reducing HIV incidence, if modified among MSM populations. Completion of these activities is expected to result in the testing of hypotheses about reasons for black/white disparities in HIV among US MSM, modeling tools that will be useful to further evaluation of MSM networks, and specific, proposed targets for new prevention interventions for this most highly impacted community in the US HIV epidemic. Our Specific Aims are: (1) to develop a comprehensive set of individual, dyadic, and triadic network parameters, accounting for transmission potential, for use in an agent-based HIV transmission model for black and white MSM in metropolitan Atlanta; (2) to expand an existing stochastic, agent-based HIV transmission model for MSM to include code for modeling network features for black and white MSM; (3) to utilize this enhanced model and parameters to (a) determine whether racial disparities for HIV observed among Atlanta-area MSM can be explained using existing hypotheses for their sources in combination with our measured network phenomena; (b) identify the highest- impact network properties for addressing racial/ethnic disparities in HIV among US MSM.

描述（由申请人提供）：在美国，黑人和白人男男性行为者（MSM）之间的艾滋病毒差异很大，且无法解释。这些差异的个人行为原因通常被认为是可能的解释。网络解释已被证明有助于理解其他人群中性传播感染负担的持续差异，并被假设可以解释美国男同性恋者的种族/民族差异。然而，由于两个原因，这些假设尚未使用建模方法进行测试。首先，历史上没有足够的数据来参数化关于关键网络特征的模型，例如并发性、传递性和关键特征的分类混合。其次，还没有发展出模型结构来解释男男性接触者性网络的独特方面。我们建议通过分析调查人员在亚特兰大进行的多项研究中关于男男性接触者性网络的新数据来加深这一理解。亚特兰大是一个拥有大量黑人和白人男男性接触者的大都市地区，在艾滋病毒方面存在显著的种族差异。我们将召回当前和近期研究的参与者，以收集更多的信息