Tracking population-based HIV transmission dynamics is critical to design and monitor effective interventions. Despite widespread prevention, HIV incidence has failed to decline among some subgroups in the United States (US) including young men who have sex with men (MSM). Such disparities are notable in the Southern US which is at the epicenter of the national epidemic with the greatest burden in new and prevalent infections. Significant disparities in HIV infection exist based on race/ethnicity and risk behaviors, but also in geography; a higher proportion of cases are reported outside large urban areas compared to other regions. Delineating HIV transmission dynamics in the Southern US can identify ongoing transmission networks or clusters where targeted prevention measures may be more impactful at reducing local incidence. However, the success of such measures requires timely identification and response to emerging or expanding clusters. Prospective phylogenetic analyses of HIV sequences integrated with epidemiologic and clinical surveillance data would facilitate the timely detection and monitoring of transmission networks. When combined with phylodynamic modeling, cluster expansion and transmission dynamics could be better predicted and the impact of interventions assessed. Our overall hypotheses are: 1) Prospective phylogenetic cluster analysis allows timely identification of transmission chains not apparent through routine surveillance, 2) Persons identified in expanding clusters represent the leading edge of local transmission, i.e. recent infection, 3) Targeting prevention towards growing clusters will identify a higher proportion of recent infections and ultimately reduce incidence. These hypotheses will be addressed in North Carolina (NC) with three specific aims:
Aim 1 : To describe the demographic and geographical characteristics of HIV transmission involving persons with newly reported HIV infection using phylogenetic clustering, viral load, and risk behaviors;
Aim 2 : To assess HIV cluster expansion and inform phylodynamic models by integrating large-scale deep sequencing and contact networks involving cases with newly diagnosed HIV infection;
Aim 3 : To conduct a preliminary assessment of a cluster-directed partner services intervention to interrupt HIV transmission networks.
These aims will be addressed through a combination of strategies in collaboration with the NC Department of Health and Human Services. A statewide prospective, automated cluster analysis system (nextHIV) will be evaluated. Sequences from reference laboratories and deep sequencing of diagnostic specimens from public testing sites will be analyzed in near-real time. Clusters will be characterized with detailed epidemiological data including HIV viral loads and contact networks. A proof-of-concept, cluster-directed partner services intervention will be assessed in an 11 county region with high HIV burden. Phylodynamic and mathematical modeling will be used to assess cluster expansion and the potential impact of interventions.
HIV transmission continues in the Southern US despite comprehensive prevention. New strategies are needed to detect and respond to ongoing transmission networks to ultimately reduce HIV incidence. Combining epidemiological data, HIV sequence analyses, and mathematical modeling into an automated surveillance system can provide timely detection of networks and help assess the impact of interventions.
