Assessing the Impact of COVID-19-Related Distancing and Clinical Service Disruptions on the HIV Epidemic in the United States

项目摘要 目前有超过120万美国人感染了人类免疫缺陷病毒（HIV）， 尽管每年都有新的感染病例，但艾滋病毒仍然是美国的一个主要公共卫生挑战。艾滋病风险不是 在美国人口中是一致的：大约70%的感染发生在同性恋、双性恋和其他男性中。 男男性行为者（MSM）和某些种族/族裔群体的艾滋病毒感染风险较高。艾滋病毒传播 尽管最近在生物医学预防和治疗方面取得了进展， 在获得这些措施方面的差距。2019冠状病毒病全球大流行对经济和社会造成的破坏 加剧了这些差距，并在艾滋病毒控制方面带来了新的挑战， 预防和临床护理服务，促进重大行为改变（包括减少性行为）， 性距离（sexual distancing）。这些变化可能会极大地影响美国艾滋病毒流行的轨迹。 有报告称，在大流行期间，艾滋病毒诊断减少，但这些估计可能是一个假设。 减少的筛选而不是减少的传输的伪影，因此是不可靠的。枚举 艾滋病毒的传播对于提供艾滋病毒预防干预措施至关重要;更好地了解艾滋病毒传播的方式， COVID-19大流行已经并将继续影响美国MSM的艾滋病毒动态，这是迫切需要的。 由于服务中断而增加的传播可能会被性距离抵消，但这取决于 这些变化的时间模式和人口分布。还可以通过以下方式减轻传播 解决临床中断的干预（例如，远程保健和其他家庭艾滋病毒医疗服务）。 我们的总体假设是：1）与COVID-19相关的性行为变化和服务中断 美国男男性接触者在人口统计学因素的影响程度和时间上各不相同，2）这些变化将改变艾滋病毒 大流行时期的发病率，以及3）有针对性的以家庭为基础的艾滋病毒医疗护理保留干预措施， 减少临床护理中断对艾滋病毒传播的影响。在AIM 1中，我们将从两个 美国男男性接触者的独立纵向研究，以描述 性距离和艾滋病毒服务中断。在AIM 2中，我们将使用基于网络的HIV传播模型 解开艾滋病毒传播与筛查的变化，以估计美国男男性行为者中的艾滋病毒发病率 于2019冠状病毒病大流行期间及之后。在AIM 3中，我们将使用传输模型来确定 在高负担管辖区有针对性的家庭艾滋病毒护理保留干预措施的流行病学影响。 该项目的研究结果将为艾滋病毒监测工作提供信息，并指导制定有针对性的艾滋病毒 预防方案。通过这项研究和培训计划，申请人将获得多学科技能 结合流行病学方法，网络科学和传染病建模，同时推进我们的 了解COVID时代的艾滋病毒动态。这种独特的培训将提供所需的技术技能， 申请人成为成功的独立研究人员和传染病流行病学家。

PROJECT SUMMARY With over 1.2 million Americans currently living with Human Immunodeficiency Virus (HIV), and nearly 40,000 new infections every year, HIV remains a major public health challenge in the United States. HIV risk is not uniform across the US population: approximately 70% of infections occur among gay, bisexual, and other men who have sex with men (MSM), and certain racial/ethnic groups experience higher HIV risk. HIV transmission remains high despite recent advancements in biomedical prevention and treatment partly because of disparities in access to these measures. Economic and social disruptions from the COVID-19 global pandemic have exacerbated these disparities and created new challenges in HIV control, disrupting access to HIV prevention and clinical care services and prompting major behavioral changes (including reductions in sexual activity, “sexual distancing”). These changes may dramatically impact the trajectory of the US HIV epidemic. There have been reports of decreased HIV diagnoses during the pandemic, but these estimates may be an artifact of reduced screening rather than decreased transmission and are therefore unreliable. Enumerating HIV transmission is critical for the provision of HIV prevention interventions; a better understanding of how the COVID-19 pandemic has affected and will continue to affect HIV dynamics of US MSM is urgently required. Increased transmission due to service disruptions may be offset by sexual distancing, but this depends on the temporal patterns and demographic distribution of these changes. Transmission may also be mitigated by interventions that address clinical disruptions (e.g., telehealth and other home-based HIV medical services). Our overarching hypotheses are: 1) COVID-19-related changes in sexual behavior and service disruptions have varied among US MSM in magnitude and timing by demographic factors, 2) these changes will alter HIV incidence across the pandemic era, and 3) targeted home-based HIV medical care retention interventions can curtail the impact of clinical care disruptions on HIV transmission. In AIM 1, we will triangulate data from two independent longitudinal studies of US MSM to describe the temporal patterns and demographic distribution of sexual distancing and HIV service disruptions. In AIM 2, we will use a network-based HIV transmission model to disentangle changes in HIV transmission versus screening to estimate HIV incidence among US MSM during and after the COVID-19 pandemic. In AIM 3, we will use a transmission model to determine the epidemiologic impact of targeted home-based HIV care retention interventions in a high burden jurisdiction. The findings of this project will both inform HIV surveillance efforts and guide the development of targeted HIV prevention programs. With this research and training program, the applicant will gain a multidisciplinary skill set combining epidemiologic methods, network science, and infectious disease modeling, while advancing our knowledge of HIV dynamics in the COVID era. This unique training will provide the technical skillset needed for the applicant to become a successful independent researcher and infectious disease epidemiologist.