CROI 2020 Abstract eBook

Abstract eBook

Poster Abstracts

the geospatial dynamics of the HIV epidemics across mainland France to identify factors associated with HIV dispersal for guiding prevention efforts. Methods: We applied a multistep phylogenetic approach on a large set of HIV-1 pol sequences from PHI individuals diagnosed in mainland France in ANRS AC43 laboratories performing genotypic resistance tests between 2014-2017: (1) We first performed an overall maximum likelihood phylogenetic inference to identify well-supported monophyletic clades; (2) All clades of size≥3 were used to perform a discrete phylogeographic inference to evaluate the dispersal history across mainland France; (3) We then applied a generalized linear model (GLM) to test the association of demographic, geospatial factors and connectivity (i.e. geographic distances and the intensity of air traffic passenger flow) with lineage dispersal. Results: A total of 1,545 pol sequences were collected. After combining these with 48,658 publicly available sequences, we identified 71 clusters from 37 counties. The discrete phylogeographic analysis revealed varying levels of virus exchange between counties (Fig.A). The GLM analysis revealed that viral migration was strongly associated with limited driving time (BF=142, Fig.B). These observations illustrate the HIV dynamics across mainland France with Paris and Lyon areas (the 2 largest cities) being major sources and recipients of viral dispersal. It suggests the role of local human migration and large urban area in sustaining the HIV epidemics. Conclusion: The combined use of phylogeography and GLM provides deeper insights into geospatial transmission patterns and factors associated with viral flows. Phylogeographic analyses confirm that highly populated areas could have a gravity effect on the French epidemic. These results may help to more efficiently allocate prevention resources and will allow to evaluate the impact of changes in demographic trends and policies.

areas not previously funded to collect sequences (3% to 27%). Of 194 priority clusters identified during December 2015–March 2019, 87 were first detected in 2018–19. Of 756 people in these 87 clusters, 71%were MSM and 11%were PWID; 53% resided in EHE areas at diagnosis. State-by-state analysis showed tremendous variation in risk and racial/ethnic groups included in clusters of rapid transmission (Figure). Conclusion: Sequence completeness has increased nationwide. Molecular cluster analysis demonstrates ability to identify recent and rapid transmission in varied populations, including capacity for detecting the rapid transmission among PWID that has occurred in recent years. Molecular cluster detection offers an opportunity for a focused, local approach to identify populations experiencing rapid transmission and tailor response to scale up services for these populations. These results demonstrate great potential for public health response to clusters and outbreaks in jurisdictions identified for the EHE Initiative.

Poster Abstracts

908 STATEWIDE HIV-1 TRANSMISSION CLUSTER DETECTION AND PRIORITIZATION FOR RESPONSE

Ann M. Dennis 1 , Simon Frost 2 , Andrew E. Cressman 1 , Shuntai Zhou 1 , Ronald Swanstrom 1 , William C. Miller 3 , Joseph J. Eron 1 , Myron S. Cohen 1 , Victoria L. Mobley 4 , Erika Samoff 4 1 University of North Carolina at Chapel Hill, Chapel Hill, NC, USA, 2 Cambridge University, Cambridge, UK, 3 The Ohio State University, Columbus, OH, USA, 4 North Carolina Division of Public Health, Raleigh, NC, USA Background: New HIV diagnoses continue in the Southern US despite widespread prevention efforts, underscoring the need for innovative deployment of prevention tools. Detection and response to genetically clustered infections is a pillar to the Ending the Epidemic initiative. We combined viral load (VL) and surveillance data to prioritize genetic clusters where re- engagement to care activities could be intensified. Methods: We developed automated cluster analyses to prospectively monitor clusters in North Carolina; the system is routinely updated with pol sequences (from clinical and public testing sites), demographic, and clinical data. Clusters were constructed from pairwise genetic distances (TN-93), connecting edges <1.5% difference. Prioritization metrics were assessed for clusters with recent diagnoses (2017-2019) and based on the adjacent nodes to recent diagnoses (edges <1.5%), including members potentially disengaged from care (“Prompt” cases). Prompt cases were defined as members without VLs or persistent/rising viremia (VL>200 c/mL) in the prior 12 months. Connectivity of Prompt cases in clusters was estimated by number of edges to all adjacent nodes (i.e. node degree) per prompt case. Results: Of 15,558 persons with 25,509 sequences in the pipeline, 2195 had recent diagnoses; 59% (1294) of these were identified in 532 clusters. Clusters involved 2512 members: 1218 (48%) were past diagnoses (≤2016). Recent diagnoses in clusters were more likely to be MSM (65% vs. 46%), younger (33% vs. 15% 18-24 years), and have acute infection (9% vs. 5%) compared to non- clustered recent diagnoses (all p<0.01). Recent diagnoses tended to cluster with other recent diagnoses: 60% (775) clustered with ≥3 recent diagnoses (range 3-28). However, most clusters (65%) involved ≥1 Prompt case and the Prompt connectivity was associated with more recent diagnoses in clusters (Figure). A prioritization threshold of ≥5 recent diagnoses and connectivity ≥5 per cluster,

907 INCREASING CAPACITY FOR DETECTING CLUSTERS OF RAPID HIV TRANSMISSION: UNITED STATES

Alexandra M. Oster 1 , Nivedha Panneer 1 , Sheryl Lyss 1 , Neeraja Saduvala 2 , Tianchi Zhang 2 , Cheryl B.Ocfemia 1 , Laurie Linley 1 , Meg Watson 1 , Robert P. McClung 1 , WilliamM. Switzer 1 , Joel O.Wertheim 3 , Ellsworth M. Campbell 1 , Angela L.Hernandez 1 , Anne Marie France 1 1 CDC, Atlanta, GA, USA, 2 ICF International, Atlanta, GA, USA, 3 University of California San Diego, San Diego, CA, USA Background: Responding to HIV clusters and outbreaks is a pillar of the U.S. Ending the HIV Epidemic (EHE) initiative, which will initially focus on 48 counties; Washington, D.C.; San Juan, Puerto Rico; and 7 states with substantial rural burden. Molecular cluster detection uses HIV sequence data and can identify rapid transmission for public health response; in 2015–2016, most persons involved in U.S. clusters were men who have sex with men (MSM)— only 1%were persons who inject drugs (PWID). In 2018, requirements to collect HIV sequence data expanded from 27 to all CDC-funded health departments. We described changes in molecular cluster detection capability in EHE and non-EHE areas and geographic variation in transmission dynamics. Methods: We examined HIV-1 polymerase sequence completeness in the National HIV Surveillance System from December 2015 (first implementation of molecular cluster detection) to March 2019 for people with HIV diagnosed in the past 3 years. Clusters of rapid transmission were identified quarterly among people with HIV diagnosed in the past 3 years using HIV-TRACE with a pairwise genetic distance threshold of 0.5%. Priority clusters had ≥ 5 diagnoses in the past 12 months. We described people in clusters first detected in 2018–19 after expansion of reporting. Results: Sequence completeness increased from 26% (December 2015) to 42% (March 2019); increases were seen in EHE areas (30% to 43%) and in

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