Novel threat detection methodology to detect HIV outbreaks in Washington

摘要/摘要 尽管最近在生物医学艾滋病毒预防方面取得了重大进展，但华盛顿州的艾滋病毒诊断率 在过去几年中保持稳定，2014年为5.3/10万，#年为5.4/100,000 2018年。识别和应对疫情是公共卫生实践的基石；快速公共卫生 在这种情况下采取行动可能会减少艾滋病毒和其他传染病的传播。而这些中心 疾病控制和预防中心(CDC)要求当地卫生部门进行分析以确定 艾滋病毒分子群和/或新艾滋病毒诊断的时空群，最近没有艾滋病毒暴发 由注意到病例增加的当地卫生部门工作人员或提供者以外的其他方法确定 特定的地区或人口。 我们与华盛顿州卫生部(DOH)合作，提出以下建议 旨在评估一种识别艾滋病毒爆发的新方法：(1)适应快速威胁检测 由我们的团队开发的方法，用来识别淋病的暴发，而不是识别空间- 艾滋病毒病例的时间集群，或华盛顿州以前确定的集群的变化，基于 来自多个县的回溯性数据，以及(2)将此方法的性能与 华盛顿卫生部目前使用的集群识别方法的性能，包括疾控中心 分子和时空集群识别的推荐策略。我们将确定这是否 方法可以比CDC推荐的常规方法更早地识别疫情，包括 2018年在华盛顿州金县注射吸毒者中爆发的艾滋病毒。 我们提出了一种创新的方法，这些方法是在统计变化检测的基础上进行改编和扩展的 以及时空方法，以快速识别集群的时间和位置。如果我们的方法是 被发现为华盛顿卫生部正在进行的工作提供附加值，我们将帮助实施该方法，以便 它可以与华盛顿州的艾滋病毒监测结合使用。虽然我们的方法不依赖于 关于艾滋病毒基因序列信息，如果成功，它还可以用来帮助识别更合适的 确定艾滋病毒分子簇的本地标准。这种方法是灵活的，可以应用于许多 情景，包括梅毒或SARS-CoV-2等其他感染。

Abstract/summary Despite recent significant advances in biomedical HIV prevention, HIV diagnosis rates in Washington State have been stable over the past several years, with a rate of 5.3 per 100,000 in 2014 and 5.4 per 100,000 in 2018. Identifying and responding to outbreaks is a cornerstone of public health practice; rapid public health action in such cases may decrease the transmission of HIV and other infectious diseases. While the Centers for Disease Control and Prevention (CDC) require that local health departments conduct analyses to identify HIV molecular clusters and/or time-space clusters of new HIV diagnoses, no recent HIV outbreaks have been identified by methods other than local health department staff or providers noticing increases in cases in specific areas or populations. Working in collaboration with the Washington State Department of Health (DOH), we propose the following aims to evaluate a new methodology to identify HIV outbreaks: (1) To adapt rapid threat detection methodology that was developed by our team to identify outbreaks in gonorrhea to instead identify spatial- temporal clusters of HIV cases, or changes in previously identified clusters in Washington State, based on retrospective data from multiple counties, and (2) To compare the performance of this methodology to the performance of current cluster identification methods being used by the Washington DOH, including CDC recommended strategies for molecular and time-space cluster identification. We will determine whether this method could have identified outbreaks sooner than the routine, CDC-recommended approaches, including an HIV outbreak that occurred among injection drug users in King County, WA in 2018. We propose an innovative approach; the methods are adapted and expanded from statistical change detection and spatiotemporal approaches to identify the time and location of the clusters rapidly. If our approach is found to provide added value to ongoing work at Washington DOH, we will help implement the approach so that it can be used in conjunction with HIV surveillance in Washington State. While our approach does not rely on HIV genetic sequence information, if successful, it can also be used to assist in identifying more appropriate local criteria to identify HIV molecular clusters. This approach is flexible and can be applied in numerous scenarios, including for other infections such as syphilis or SARS-CoV-2.