Leveraging Networks, Epidemiology, and Epidemic Modeling: Creative Approaches for HIV Elimination

摘要 美国新的艾滋病毒感染开始下降，但被边缘化的群体，如 使用药物的人群继续经历新的感染。急性和非传染性疾病患者 早期艾滋病毒(AEH)和艾滋病毒感染者，但没有得到护理，是持续的关键驱动因素 变速箱。生物干预，如暴露前预防(PrEP)，可减少 90%的人感染艾滋病毒可以减少传播，但边缘化群体的使用率较低 费率。社交网络因素被认为是造成艾滋病毒感染率差异的原因 收购。公共卫生部门传统上使用接触者追踪(询问新的艾滋病毒 被诊断的客户识别性或毒品接触者)，以识别不知情的个人 关于他们感染艾滋病毒的信息，但由于报告不足，这一信息往往不完整。专家们正在 现在转向分子网络数据(通过类似的HIV-1 Poll序列连接的个人) 与艾滋病毒疫情应对的接触者追踪信息相结合。虽然消息灵通， 抽样挑战限制了对这些来源的依赖，以作出关于艾滋病毒的推断 变速箱。相比之下，社交网络数据比性接触数据更完整， 通常包括网络中的药物使用和性伴侣。尽管有迹象表明 在综合这些数据方面，很少有人研究如何将它们整合起来 艾滋病毒预防和护理。这个项目的总体目标是更好地理解复杂和 参与艾滋病毒传播的重叠社会和分子网络动态，以便 更有效地优先采取干预措施，以减少艾滋病毒发病率。

Abstract New HIV infections in the U.S. are beginning to decline, but marginalized groups such as substance using populations continue to experience new infections. Individuals with acute and early HIV (AEH) and those who are HIV infected, but out of care, are key drivers of ongoing transmission. Biological interventions such as pre-exposure prophylaxis (PrEP) that reduces HIV acquisition by >90% can curtail transmission, but marginalized groups have low utilization rates. Social network factors have been noted as contributing to the difference in rates of HIV acquisition. Public health departments traditionally used contact tracing (asking newly HIV diagnosed clients to identify their sex or drug contacts) to identify individuals who are unaware of their HIV infection, but this information is often incomplete due to underreporting. Experts are now turning toward molecular network data (individuals linked by similar HIV-1 pol sequences) in conjunction with contact tracing information for HIV epidemic response. While informative, sampling challenges limit the reliance on these sources alone for making inferences about HIV transmission. Social network data, in contrast, are more complete than sexual contact data and often include substance use and sexual partners in networks. Despite indication of the benefits of combining these data, little research has been conducted on how they can be integrated for HIV prevention and care. The overall goal of this project is to better understand the complex and overlapping social and molecular network dynamics involved in HIV transmission in order to more effectively prioritize interventions to reduce HIV incidence.