Khanna Aditya S, Novitsky Vladimir, Guang August, Howison Mark, Gillani Fizza S, Steingrimsson Jon, Fulton John, Bertrand Thomas, Macaskill Meghan, Hogan Joseph, Bandy Utpala, Kantor Rami
Center for Alcohol and Addiction Studies, Brown University School of Public Health, Providence, RI, USA.
Department of Behavioral and Social Sciences, Brown University School of Public Health, Providence, RI, USA.
Open Forum Infect Dis. 2025 Jun 11;12(7):ofaf341. doi: 10.1093/ofid/ofaf341. eCollection 2025 Jul.
Evaluate added value of integrating partner services and molecular epidemiology data to disrupt HIV transmission.
Integration of statewide partner services and molecular databases.
We evaluated overlap of persons and their social/molecular links in contact tracing (Contact Tracing Database [CTDB], 2008-2022) and HIV-1 genomic (Genomic Database [GDB], 2004-2023) databases using Jaccard coefficient (JC); inferred molecular clustering using phylogeny; assessed care engagement gaps by developing a "partner naming" cascade; and explored associations of molecular clustering and partner naming using generalized estimating equations.
Among 2418 CTDB and 2527 GDB individuals, 894 (JC = 0.22) and 59 links (JC = 0.012) appeared in both databases, demonstrating low overlap. Molecular clustering occurred in 48% of all GDB persons, 65% of persons in both databases, 71% of persons providing partner data, and 88% of named partners in both databases. Of 1342 named partners, contacts were attempted for 66%, and 93% were reached; of those reached, 71% were newly HIV-tested, of whom 27% were newly diagnosed, and all newly diagnosed were sequenced. Men who have sex with men and people who inject drugs were more likely to cluster molecularly in the GDB if linked in the CTDB, while high-risk heterosexuals were less likely. Men who have sex with men and older individuals were more likely to be linked in the CTDB if they clustered molecularly, while people who inject drugs were less likely.
Comprehensive, statewide integration of contact tracing and molecular data enables public health insights not available with one source alone, underscoring the added value of data integration in identifying gaps to improve HIV prevention services.
评估整合性伴服务和分子流行病学数据对阻断艾滋病毒传播的附加价值。
整合全州范围的性伴服务和分子数据库。
我们使用杰卡德系数（JC）评估了接触者追踪（接触者追踪数据库[CTDB]，2008 - 2022年）和艾滋病毒-1基因组（基因组数据库[GDB]，2004 - 2023年）数据库中人员及其社会/分子联系的重叠情况；利用系统发育推断分子聚类；通过建立一个“性伴命名”级联来评估护理参与差距；并使用广义估计方程探索分子聚类与性伴命名之间的关联。
在2418名CTDB个体和2527名GDB个体中，两个数据库中分别出现了894人（JC = 0.22）和59个联系（JC = 0.012），表明重叠度较低。分子聚类出现在所有GDB人员的48%、两个数据库中的人员的65%、提供性伴数据的人员的71%以及两个数据库中被命名性伴的88%中。在1342名被命名的性伴中，66%尝试进行了接触，93%成功接触到；在成功接触到的人中，71%进行了新的艾滋病毒检测，其中27%被新诊断出感染，所有新诊断出的都进行了测序。在CTDB中有联系的男男性行为者和注射毒品者在GDB中更有可能出现分子聚类，而高危异性恋者则不太可能。男男性行为者和年长者如果出现分子聚类，则在CTDB中更有可能有联系，而注射毒品者则不太可能。
全面、全州范围的接触者追踪和分子数据整合能够提供仅靠单一来源无法获得的公共卫生见解，强调了数据整合在识别差距以改善艾滋病毒预防服务方面的附加价值。
