CROI 2020 Abstract eBook

Abstract eBook

Poster Abstracts

921 MOLECULAR ANALYSIS SUGGESTS POST-MIGRATION HIV-1 ACQUISITION AMONG MIGRANTS IN PARIS Evangelia G. Kostaki 1 , Cathia Soulie 2 , Benoit Visseaux 3 , Alexandre Storto 3 , Charlotte Charpentier 3 , Marc Wirden 2 , Roland Landman 4 , Christine Katlama 2 , Vincent Calvez 2 , Diane Descamps 3 , Federico García 5 , Maria M. Santoro 6 , Dimitrios Paraskevis 1 , Anne-Geneviève Marcelin 2 1 University of Athens, Athens, Greece, 2 AP–HP, Hôpitaux Universitaires Pitié Salpêtrière, Paris, France, 3 AP–HP, Hôpital Bichat-Claude Bernard, Paris, France, 4 IMEA, Paris, France, 5 Hospital Universitario San Cecilio, Granada, Spain, 6 University of Rome Tor Vergata, Rome, Italy Background: Almost half of the new HIV diagnoses were among people originating from outside the reporting country (migrants) in Europe the last few years. We aimed to trace the geographic origin of HIV-1 CRF02_AG infections, the most prevalent non-B clade in France, for migrants in Paris, using molecular epidemiology methods. Methods: We studied the first available pol gene sequence for all patients infected with HIV-1 CRF02_AG (N=2,146) diagnosed in two large Parisian University hospitals. HIV-1 subtyping was carried out using automated subtyping tools (COMET, REGA). We analyzed phylogenetically the CRF02_AG sequences frommigrants (N=567) along with all the available CRF02_AG sequences from non-migrant patients (N=1,579). We also included all publicly available CRF02_AG sequences (N=3,476), and unpublished CRF02_AG sequences from Spain, Italy and Greece (N=1193), as references. Local transmission networks (LTNs) were phylogenetic clusters including sequences from France at proportions >70%, receiving bootstrap value >70% or SH- support >0.8. Phylogenetic trees were estimated by the maximum likelihood method (RAxML, FastTree). The origin of HIV-transmissions was traced by phylogeographic analysis using the criterion of parsimony (Mesquite). Results: Phylogenetic analysis revealed that 198 (34.9%) sequences from migrants clustered within LTNs. The distribution of transmission risk group in migrants infected with CRF02_AG strains was: Heterosexuals (N=447; 78.8%), MSM (N=37; 6.5%), Others/Unknowns (N=83; 14.7%). The proportion of migrant MSM within CRF02_AG LTNs was significantly higher (83.8%) than the corresponding proportion of heterosexuals (31.5%) (p<0.001). Phylogeographic analysis showed that 29.3% of the CRF02_AG HIV-transmissions within migrants occurred in France. Multivariate analysis showed that parameters associated with clustering within the large LTNs (≥10 sequences) were MSM risk group (MSM vs heterosexuals OR: 10.3, 95% CI: 6.5-16.5) and French origin (non-migrants vs migrants OR: 2.4, 95% CI: 1.5-3.9). Conclusion: We found that 29.3% of CRF02_AG HIV-transmissions within migrants originated in Paris. Transmissions among migrants within LTNs were associated with MSM risk group. Moreover, transmissions within large clusters are more frequent among MSM and non-migrants. This is one of the fewmolecular studies showing that even for CRF02_AG, which is prevalent in Sub-Saharan Africa, a large proportion of transmissions among migrants occur in Paris. 922 GEOGRAPHIC PATTERNS IN HIV TRANSMISSION CLUSTERS IN LOS ANGELES COUNTY Britt Skaathun 1 , Manon Ragonnet-Cronin 1 , Kathleen Poortinga 2 , Zhijuan Sheng 2 , Yunyin W. Hu 2 , Joel O.Wertheim 1 1 University of California San Diego, La Jolla, CA, USA, 2 Los Angeles County Department of Public Health, Los Angeles, USA Background: Clusters of HIV transmission can serve as alerts for public health action. These clusters can comprise (i) geographic clusters of diagnosis in time and space or (ii) clusters of genetically linked cases. We assessed the impact of geography across the Los Angeles County (LAC) HIV genetic transmission network and its relevance to directing HIV prevention and treatment. Methods: Deidentified surveillance data reported for 8150 persons residing in LAC (2010 through 2016) were used to construct a transmission network using HIV-TRACE. Persons were linked if their pairwise genetic distance was ≤0.015 substitutions/site. Residential information at diagnosis was examined at ZIP code, health district (HD), and service planning area (SPA). We used 3 approaches to characterize this relationship: (i) geographic assortativity, the tendency for people to link to others within the same geography (ii) concordant time-space pairs, the proportion of genetically linked pairs from the same geography and diagnosis year, and (iii) Jaccard coefficient (JC), the intersection divided by the union of geography and cluster sets. Significance was determined

using 1000 random network permutations. A generalized linear model was used to identify characteristics associated with the JC. Results: The 4150 (50.6%) HIV cases that were clustered were assortative by ZIP, HD, and SPA (0.02, 0.09, 0.15; p<0.001). Geography was less assortative than race/ethnicity and transmission risk. 58% of genetically linked cases were diagnosed in the same year, and 44%were diagnosed in the same HD; however, only 19%were diagnosed in the same year and HD. This time-space concordance among genetically-linked pairs was also low across ZIP and SPA (p<0.001). In the JC analysis, cis-men (b=0.20; p<0.001) and those younger at diagnosis (b=0.189; p=0.01) had more overlap between clusters and geography; we observed an inverse association for trans-women (b=-0.51; p<0.001) and African-Americans (b=-0.18; p<0.001). Conclusion: We found significant, but weak associations between the HIV transmission network and residence at diagnosis. Within an urban setting with endemic HIV, genetic clustering may serve as a better indicator than time-space clustering to understand transmission patterns and direct public health action.

Poster Abstracts

923 HUMAN MOBILITY PATTERNS GENERATE GEOGRAPHICALLY STRUCTURED SUB-EPIDEMICS IN NAMIBIA Eugenio Valdano 1 , Justin Okano 1 , Vittoria Colizza 2 , Sally Blower 1 1 University of California Los Angeles, Los Angeles, CA, USA, 2 INSERM, Paris, France Background: Populations in Sub-Saharan Africa are highly mobile. Therefore, an individuals’ “social/sexual community” can consist of multiple communities: we define such a social/sexual community as a mega-community (MC). If MCs exist, they would geographically structure a generalized HIV epidemic into loosely connected sub-epidemics. This would have significant implications for designing effective epidemic control strategies. Here we use mobile phone data from Namibia, where HIV prevalence is ~14%, to search for MCs. Methods: Call detail records (CDRs) were collected from 90% of subscribers in Namibia over a 12-month time period; they represent 9 billion communications from 1.19 million unique SIM cards. We analyzed these data at the constituency level, from all constituencies with cell towers: 96 out of 110. Our analyses enabled us to discover countrywide travel patterns, and determine howmuch time travelers from each constituency spent in other constituencies. We then used a technique from network science (a community-detection algorithm) to determine if MCs exist. Results: Residents of Namibia spent ~22% (median, Interquartile range: 18-26%) of their time outside their home constituency, over a year. Population- level travel patterns divide Namibia’s population of 2.5 million into eight MCs that vary in size (15,000 to 650,000 individuals) and compactness (figure). Namibia’s generalized epidemic consists of eight connected sub-epidemics: each contained within a MC. We were also able to identify “bridges” that link sub-epidemics: a bridge is a constituency in one MC that is linked, by travel, to another MC. We identified two “types” of bridges (figure): short bridges (linked constituencies are spatially contiguous) and long bridges (linked constituencies are separated by at least one constituency). Notably, the capital of Namibia (Windhoek) is a long bridge and connects to six MCs and sub-epidemics. Oshakati, the capital of one of 14 regions in Namibia, is also a long bridge; it is connected to five MCs and sub-epidemics. Conclusion: As a result of travel patterns, the population of Namibia is divided into MCs. These MCs are not visible, but they spatially structure Namibia’s

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