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Automation and Evaluation of Real-Time Transmission Network-Based HIV Prevention Services in New York City

纽约市基于实时传输网络的艾滋病毒预防服务的自动化和评估

基本信息

批准号：
10308047
负责人：
Joel Okrent Wertheim
金额：
$ 66.69万
依托单位：
UNIVERSITY OF CALIFORNIA, SAN DIEGO
依托单位国家：
美国
项目类别：
财政年份：
2018
资助国家：
美国
起止时间：
2018-01-24 至 2024-12-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10308047
关键词：
AIDS prevention Address Automation California Caring Centers for Disease Control and Prevention (U.S.)Cities Clinic Collaborations Country County Data Demography Diagnosis Drug resistance Epidemic Epidemiology Evaluation Future Genetic Genotype Geography Goals Growth Guide prevention HIV HIV Infections HIV Seronegativity HIV Seropositivity HIV diagnosis HIV-1 Health Health Resources Individual Infection Infrastructure Intervention Laboratories Lead Link Location Mental Health Methods Molecular Monitor Names Network-based New York City Newly Diagnosed Observational Study Outcome Partner Notification Persons Physicians Plant Roots Prevention Protocols documentation Provider Public Health Reporting Research Design Risk Factors Scheme Secure Sequence Analysis Services Specific qualifier value System Testing Time United States United States Public Health Service Universities Viral Work antiretroviral therapy base burden of illness care systems high risk improved indexing pre-exposure prophylaxis prevent prevention service programs rapid growth screening standard of care therapy adherence transmission process trend virus genetics web app

项目摘要

ABSTRACT Introduction. The HIV epidemic in the United States persists. Public health departments across the country are exploring how to better use viral genetic sequence data to reconstruct transmission networks and guide prevention efforts. In 2017, the Centers for Disease Control and Prevention (CDC) and University of California, San Diego (UCSD) unveiled a nationwide initiative, Secure HIV-TRACE, to allow public health departments to construct genetic transmission networks in near-real time. Concurrently, the New York City (NYC) Public Health Labs (PHL) began sequencing viral genotypes themselves (i.e., point-of-diagnosis genotyping) for people diagnosed by select providers, in order to reduce the time between diagnosis and sequence analysis. The goal of this these programs are to direct standard pubic health resources in near real-time to cases, clusters, and locations of greatest concern (i.e., greatest potential for future cases). The underlying assumption of this strategy is that prioritization based on cluster growth dynamics inferred from genetic sequence data will disproportionately reduce future disease burden. Therefore, the important question is not whether real-time time targeting can prevent incident infections; rather, the important question is: Can real-time targeting prevent more incident infections than current, network-agnostic public health strategies? Methods. Here, we propose an observational study designed to evaluate the impact of these real-time strategies, which are currently implemented in NYC. We will automate Secure HIV-TRACE to construct genetic transmission clusters in real- time to guide standard public health services in NYC. Using these clusters, we will identify Index Cases (i.e., HIV-infected people diagnosed by select provides who receive point-of-diagnosis genotyping by PHL) and then to identify Priority Partners (i.e., in-care viremic or out-of-care HIV-infected partners, genetically linked to the Index Case). Standard public health services will then be offered to these Priority Partners [e.g., return to care, antiretroviral therapy (ART) adherence support, partner elicitation services]. Using data routinely reported to NYC Department of Health and Mental Hygiene, we will assess whether these services provided to Priority Partners lead to (i) increased rates of viral suppression in the Priority Partners, (ii) less than predicted incident HIV cases in their transmission cluster, (iii) an interaction with past cluster growth to result in even less than predicted incident HIV cases in their transmission cluster, and (iv) an interaction with past cluster growth to identify more than predicted prevalent, undiagnosed HIV cases in their transmission cluster. Conclusions. If we observe an interaction between past cluster growth and public health outcomes resulting from standard prevention services, this will suggest that real-time network based prevention should become standard of care in NYC and beyond. Through Secure HIV-TRACE, we can expand this scope approach nationwide.

抽象的介绍。美国的艾滋病毒流行持续存在。全国各地公共卫生部门正在探索如何更好地利用病毒基因序列数据重构传播网络并指导预防工作。 2017 年，美国疾病控制与预防中心 (CDC) 和加州大学，圣地亚哥（UCSD）推出了一项全国性倡议“Secure HIV-TRACE”，以允许公共卫生部门近乎实时地构建遗传传输网络。同时，纽约市 (NYC) 公众健康实验室 (PHL) 开始对病毒基因型本身进行测序（即诊断点基因分型）由精选的提供者诊断的人，以减少诊断和序列分析之间的时间。这些计划的目标是将标准公共卫生资源近乎实时地引导到病例，集群和最受关注的地点（即未来病例的最大潜力）。基本假设该策略的核心在于，基于从基因序列数据推断的簇生长动态的优先级将不成比例地减少未来的疾病负担。因此，重要的问题不是是否实时时间目标可以防止事件感染；相反，重要的问题是：实时定位能否防止比当前与网络无关的公共卫生策略更多的事件感染？方法。在此，我们建议一项观察性研究，旨在评估这些实时策略的影响，这些策略目前正在在纽约市实施。我们将自动化 Secure HIV-TRACE 来构建真实的基因传播集群是时候指导纽约市的标准公共卫生服务了。使用这些集群，我们将识别索引案例（即由接受 PHL 诊断点基因分型的精选提供者诊断出的 HIV 感染者），然后确定优先合作伙伴（即，在护理中病毒血症或不在护理中感染艾滋病毒的伴侣，与索引案例）。然后将向这些优先合作伙伴提供标准公共卫生服务[例如，返回护理、抗逆转录病毒治疗 (ART) 依从性支持、伴侣诱导服务]。使用定期报告的数据纽约市健康和心理卫生局，我们将评估是否向 Priority 提供这些服务合作伙伴导致 (i) 优先合作伙伴的病毒抑制率增加，(ii) 事件少于预期其传播集群中的艾滋病毒病例，(iii) 与过去集群增长的相互作用导致甚至少于预测其传播集群中的艾滋病毒病例，以及 (iv) 与过去集群增长的相互作用在其传播群中发现比预测更多的流行、未确诊的艾滋病毒病例。结论。如果我们观察到过去的集群增长与标准带来的公共卫生结果之间的相互作用预防服务，这表明基于实时网络的预防应成为护理标准在纽约市及其他地区。通过 Secure HIV-TRACE，我们可以将这一范围方法扩展到全国。

项目成果

期刊论文数量（37）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Increasing Capacity to Detect Clusters of Rapid HIV Transmission in Varied Populations-United States.

DOI：
10.3390/v13040577
发表时间：
2021-03-30
期刊：
Viruses
影响因子：
0
作者：
Oster AM;Panneer N;Lyss SB;McClung RP;Watson M;Saduvala N;Ocfemia MCB;Linley L;Switzer WM;Wertheim JO;Campbell E;Hernandez AL;France AM
通讯作者：
France AM

The Huanan Seafood Wholesale Market in Wuhan was the early epicenter of the COVID-19 pandemic.

DOI：
10.1126/science.abp8715
发表时间：
2022-08-26
期刊：
SCIENCE
影响因子：
56.9
作者：
Worobey, Michael;Levy, Joshua, I;Serrano, Lorena Malpica;Crits-Christoph, Alexander;Pekar, Jonathan E.;Goldstein, Stephen A.;Rasmussen, Angela L.;Kraemer, Moritz U. G.;Newman, Chris;Koopmans, Marion P. G.;Suchard, Marc A.;Wertheim, Joel O.;Lemey, Philippe;Robertson, David L.;Garry, Robert F.;Holmes, Edward C.;Rambaut, Andrew;Andersen, Kristian G.
通讯作者：
Andersen, Kristian G.

Forecasting HIV-1 Genetic Cluster Growth in Illinois,United States.