CROI 2019 Abstract eBook

Abstract eBook

Poster Abstracts

858 WITHDRAWN / INTENTIONALLY UNASSIGNED 859 WITHDRAWN / INTENTIONALLY UNASSIGNED 860 USING NEAR REAL-TIME MOLECULAR SURVEILLANCE TO INFORM DATA- TO-CARE IN NEW YORK CITY Lucia V. Torian 1 , Chi-Chi N. Udeagu 1 , Lisa A. Forgione 1 , Qiang Xia 1 , Joel O. Wertheim 2 , Kavita Misra 1 , Jamie Huang 1 , Jennifer Rakeman-Cagno 1 , Susan Blank 1 , Michael A. Castro 1 , Sarah L. Braunstein 1 1 New York City Department of Health and Mental Hygiene, Long Island City, NY, USA, 2 University of California San Diego, La Jolla, CA, USA Background: Molecular HIV surveillance has been proposed as a tool to augment traditional partner services and data to care (D2C) activities by adding persons with genetically proximate viruses to the pool of named partners and social network members receiving public health intervention after a new diagnosis of HIV. Methods: The New York City Department of Health and Mental Hygiene conducted a pilot project to demonstrate whether early ascertainment of viral genetic proximity between newly diagnosed and prevalent cases was feasible and resulted in timely identification of and outreach to persons in transmission networks as defined by HIV-Trace, a genetic distance-based clustering tool. Persons newly diagnosed with HIV at the city’s 8 sexual health clinics (SHC) were the Index cases; their partial pol sequences were analyzed for pairwise concordance to those of 71,189 prevalent cases using a 1.5% distance threshold. Clusters were mapped, and cluster members that were out of care for ≥13 months (OOC) or in care but viremic (>1500 copies/mm3) and their viruses immediately proximate to the Index virus were identified and prioritized for assistance with partner services and reengagement in optimal care. Results: Between June 1, 2016, and June 25, 2018, whole blood specimens from 722 persons testing preliminary positive on point-of-care rapid HIV screening were submitted to the NYC Public Health Laboratory for confirmation and resistance testing, resulting in 526 interpretable genotypes. SHCs received resistance reports and sequences were posted a median of 10 days (IQR 8-15) after specimen draw date. Pairwise concordance analysis of the Index virus against the prevalence pool yielded a total of 225 clusters containing 2,778 unique members. Clusters ranged in size from 2-155 persons with diagnosis dates from 1981-2018, of whom 122 (4%) were deemed by surveillance to be currently OOC and 132 (5%) viremic; 91% of cluster members were MSM; clusters were homogeneous with respect to age at diagnosis (median 26) and race/ ethnicity but not by neighborhood of residence. Conclusion: Despite our optimized scenario (genotype ordered on day of diagnosis), cluster data were not available at the time of the Index partner services interview. However, analysis performed as soon as the sequence was posted allowed us to identify and prioritize for outreach previously diagnosed, genetically proximate OOC and viremic cluster members on a monthly basis, making it possible to achieve “near real-time” D2C for genetic partners. 861 MAPPING GROWTH OF LARGE TRANSMISSION NETWORKS USING DIFFERENT CLUSTERING ALGORITHMS Nathan Osman 1 , Antoine Chaillon 2 , Ruxandra-Ilinca Ibanescu 3 , Isabelle Hardy 4 , Irene Vrbik 5 , Bonnie Spira 1 , Luc Villandré 1 , David Stephens 1 , Michel Roger 4 , Bluma G. Brenner 1 1 McGill University, Montreal, QC, Canada, 2 University of California San Diego, La Jolla, CA, USA, 3 Lady Davis Institute for Medical Research, Montreal, QC, Canada, 4 Centre Hospitalier de l’Université de Montréal, Montreal, QC, Canada, 5 University of British Columbia, Vancouver, BC, Canada Background: Phylogenetic surveillance of the HIV epidemic amongst Men having Sex with Men (MSM) has revealed that large transmission networks (20+ infections/ cluster) rose from 13% of new infections in 2004 to 49% of infections in 2016 in Quebec. Identifying and responding to these “active” transmission hubs in close to real-time will have the greatest impact in controlling the epidemic. Methods: First genotypes were obtained from treatment-naïve MSM (n=4029) and heterosexual/intravenous drug user (IDU) (n=1072) groups having subtype B HIV-1 infections, as well as non-B subtype groups (n=1248). Unique non-nominative patient identifiers were assigned based on putative cluster group association, ascertained by Maximum likelihood (ML) methodology (high bootstrap support >97% and short genetic distance <0.015). Growth trajectories dynamics of 40 individual large transmission networks (20+

members/cluster) were compared with the San Diego-based HIV-TRACE (Transmission Cluster Engine) platform, and the Montreal-based Gap (distance- based) BD-SIR (cluster birth death), and the DM-PhyClus (Bayesian-based) methodologies. Results: Heat maps indicated overlap between estimates produced by seven clustering algorithms, revealing the role of large transmission networks in the growth of the provincial epidemic in MSM. Cluster inferences with HIV- TRACE and DM-Phys were rapid, conducive to real-time monitoring of cluster dynamics. In general, putative cluster assignments by HIV-TRACE designated at <1.5% TN93 genetic distance measures paralleled ML-based assigned. Problematic issues arose in resolving and deducing transmission links of individual members within clusters using repeat patient sampling. HIV-TRACE could not resolve two K103N and WT waves for cluster 99 and several different non-B subtypes coalesced. Conclusion: In this study, we compared the sensitivity and accuracy of different phylogenetic based methodologies in estimating transmission linkage and mapping epidemic growth in close to real-time. While several cluster-based algorithms can identify “actively” growing transmission hubs, resolving the linkage of individual members within clusters will require further optimization to maximize accuracy. 862 EPIDEMIOLOGIC CORRELATES OF HIV LINEAGE LEVEL DIVERSIFICATION RATE Angela McLaughlin 1 , P. Richard Harrigan 1 , Tetyana Kalynyak 2 , Jinny Choi 2 , Jeffrey Joy 2 1 University of British Columbia, Vancouver, BC, Canada, 2 British Columbia Centre for Excellence in HIV/AIDS, Vancouver, BC, Canada Background: Identifying risk factors and other epidemiological correlates of HIV transmission can inform the prioritization of health care services to specific groups. Typically transmission clusters are inferred based on genetic distance thresholds, then logistic regression is conducted to evaluate patient characteristics that are significantly associated with the probability of membership in an active transmission cluster. This method is limited in that all individuals within a cluster are treated as equally active transmitters, although in reality there is a range of transmission activity within a cluster. We introduce an alternative method to investigate risk factors associated with transmission in British Columbia (BC), Canada, based on the phylodynamically estimated viral diversification rate. Methods: For 8,103 people living with HIV (PLHIV) in BC in March 2018, we recovered the oldest available HIV protease and RT sequences from the BC Centre for Excellence in HIV/AIDS database. Following alignment and removal of known drug resistance sites, we inferred 100 bootstrap approximate maximum likelihood phylogenetic trees in FastTree2.1 and then time-scaled the trees using Least Squares Dating. For each tip on each bootstrap tree, we calculated the lineage level phylogenetic diversification, which provides a proxy for transmission rates. The average diversification rate of all 100 trees for each tip was taken. We then built a generalized linear model (GLM) to evaluate patient attributes that were significantly associated with higher diversification rates. Results: Having a high HIV diversification rate was positively associated with being younger, reporting injection drug use, having co-infection with hepatitis C virus, having a high most recent viral load, and residing within the Northern BC Health authority or the Vancouver Coastal Health authority (Table 1). Interestingly, having ever had AIDS and identifying as black were both significantly associated with lower diversification rates (Table 1). Conclusion: By identifying risk factors associated with HIV transmission using the viral diversification rate among PLHIV in BC, we can confidently recommend prioritized provision of treatment and prevention services for these key groups. Relative to logistic regression of phylogenetic cluster membership, this method has the added benefit of resolving finer differences in transmission activity between individuals, resulting in a more accurate assessment of risk.

Poster Abstracts

CROI 2019 335