BackgroundIn Germany, previous reports have demonstrated transmitted HIV-1 drug resistance mutations (DRM) in 10% of newly diagnosed individuals, affecting treatment failure and the choice of antiretroviral therapy (ART). Here, we sought to understand the molecular epidemiology of HIV DRM transmission throughout the Cologne-Bonn region, an area with one of the highest rate of new HIV infections in Europe (13.7 per 100,000 habitants).MethodsWe analyzed 714 HIV-1 ART naïve infected individuals diagnosed at the University Hospitals Cologne and Bonn between 2001 and 2016. Screening for DRM was performed according to the Stanford University Genotypic Resistance Interpretation. Shared DRM were defined as any DRM present in genetically linked individuals (<1.5% genetic distance). Phylogenetic and network analyses were performed to infer putative relationships and shared DRMs.ResultsWe detected 123 DRMs in our study population (17.2% of all sequences). Prevalence of any DRM was comparable among risk groups and was highest among people from an endemic area (i.e., country with HIV prevalence >1%) (11/51, 21.6%). Nucleoside-and non-nucleoside reverse transcriptase inhibitor (NRTI/NNNRTI) resistance mutations were detected in 49 (7%) and 97 (13.6%) individuals, with the E138A in 29 (4.1%) and K103N in 11 (1.5%) being the most frequent. Frequency of DRM was comparable in clustering and not clustering individuals (17.1% vs. 17.5%). Transmission network analysis indicated that the frequency of DRM in clustering individuals was the highest in PWID (3/7, 42.9%) (Figure 1A). Genetically linked individuals harboring shared DRMs were more likely to live in suburban areas than in Central Cologne (18.8% vs. 8% of clustering sequences with DRM; Figure 1B).ConclusionThe rate of DRMs was exceptionally high in the Cologne/Bonn area. Network analysis elucidated frequent cases of shared DRMs among genetically linked individuals, revealing the potential spread of DRMs and the need to prevent onward transmission of DRM in the Cologne-Bonn area. Disclosures M. Hoenigl, Gilead, Basilea, Merck: Speaker’s Bureau, Research grant and Speaker honorarium.

BackgroundGeographical targeting of interventions of hotspots of HIV transmission increases the impact of HIV intervention. We combined molecular epidemiology and geospatial analyses to provide insights into the drivers of HIV transmission and the contribution of geographical hot spots to the rapidly evolving local HIV epidemic of Cologne-Bonn.MethodsWe included 714 HIV-1-infected ART naïve individuals, followed at the University Hospitals Cologne and Bonn between 2001 and 2016. Phylogenetic and network analyses were performed to infer putative relationships. Assortativity index (AI, i.e., shared attributes) and characteristics of genetically linked individuals were analyzed. The geospatial diffusion of the local epidemic (i.e., viral gene flow) was evaluated using a Slatkin-Maddison approach. Geospatial dispersal of local HIV transmission was determined by calculating the average distance between genetically linked individuals (centroids of 3-digit zip code of residency, ArcGIS®).ResultsOf 714 sequences, 217 (30.4%) had a putative linkage with at least one other sequence, forming 77 clusters (size range: 2–8). Genetically linked individuals were significantly more likely to live in suburban areas (P = 0.035), <30 years of age (P = 0.013), infected with HIV-1 subtype B (P = 0.002). AI for concurrent area of residency showed that individuals were nonassortative in the network (−0.0026, P = 0.046), indicating that clustering individuals tended to cluster with individuals living in a different zip code. Geospatial analyses revealed that the median distance between genetically linked individuals was 23.4 km, significantly lower than expected (median 39.68 km; P < 0.001) (Figure 1A). Slatkin Maddison analyses revealed increased gene flow originating from Central Cologne toward the surrounding areas (P < 0.001, Figure 1B).ConclusionPhylogeographic analysis suggests that central Cologne may be a significant driver of the regional epidemic. While clustering individuals lived closer than unlinked individuals, they were less likely to be linked to others from their same zip code. This may reflect individuals reaching out of their neighborhoods and social circles to meet new partners. Disclosures All authors: No reported disclosures.