CROI 2015 Program and Abstracts

Abstract Listing

Poster Abstracts

248 Exploring Transmission Dynamics of HIV in Rural KwaZulu-Natal, Using Phylogenetics EduanWilkinson 1 ; Siva Danaviah 1 ; Justen Manasa 1 ; FrankTanser 1 ; Kobus Herbst 1 ; Deenan Pillay 2 ; Tulio de Oliveira 1 On behalf of the PANGEA_HIV Consortium 1 University of KwaZulu-Natal, Durban, South Africa; 2 University College London, London, United Kingdom

Background: Despite antiretroviral rollout, HIV incidence remains high in South Africa. We have observed significant social and geographical heterogeneity in HIV incidence in rural KwaZulu-Natal (Tanser et al. Science 2013). We sought to utilise phylogenetics to better understand the drivers of ongoing transmission in this hyperendemic population. Further, we explore the utility of sampling a fraction of infections to discern changes in incidence, through phylodynamic approaches. Methods: Viral load was measured in on 2,420 dried blood spots (DBS) testing positive in the population-based surveillance of 2011 and 2012. 749 partial HIV-1 pol gene sequences were obtained from DBS samples with a viral load (VL) >10,000. 900 samples were targeted for genotyping (86.0% success rate). Sequences were analysed against all reference strains from South Africa and manually edited prior to phylogenetic inference. The inferred phylogenies were analysed to identify clusters of low genetic diversity ( ≤ 0.05) corresponding to transmission clusters/pairs, defined by branch support > 98.0%. Clinical, demographic, socio-economic and geographic characteristics of infected individuals were analysed against identified clusters to discern traits associated with transmission. Molecular clock and coalescent analyses were performed in a Bayesian framework order to identify the origin of the clusters and the rate of expansion of the epidemic. Results: A total of 54 transmission clusters were identified containing 91 women and 37 men. The mean size of clusters was 2.39 (variation 2 - 13). The mean age of women in clusters was 31.55 years and of men, 35.91 years. 24.8% of individuals within the genotypic clusters were recently infected though they comprise approximately 5 % of the cohort. GIS results support the scenario of ‘hotspots’ of transmission, while coalescent analyses provide further evidence that HIV incidence is decreasing in this population.

Figure: A) We have used spatial analytical techniques to demonstrate substantial heterogeneity in the epidemic. In terms of HIV-incidence, two high-risk, overlapping spatial clusters were identified in peri-urban communities near the national road. Although the clusters comprise just 5.7% of the study area, they account for nearly one out of every three sero- conversions observed. B) We used genomics data to link HIV-1 infections. The majority of the linkages point to the previously identified hotspots suggesting that those are driving transmission to other areas. Dots represent genotyped individuals. Lines represent linkage. Conclusions: These results demonstrate the underling complex nature of the dynamics of HIV transmission and that acutely infected patients may disproportionately contribute towards transmissions in the era of increase ARVs. The use of genotypic data coupled with detailed patient information can be used to identify and characterise HIV transmission events. The use of genotypic data analysed within a phylodynamic framework also reflects the decreasing trends in incidence likely due to the scale-up of treatment coverage in recent years. 249 Detecting Changes in Incidence Using Phylogenetic Tools: Simulation-Based Studies Within the PANGEA_HIV Initiative Emma B. Hodcroft 1 ; Oliver Ratmann 2 ; Anne Cori 2 ; Mike Pickles 2 ; Samantha Lycett 3 ; Manon L. Ragonnet-Cronin 1 ; Matthew Hall 1 ; Andrew J. Leigh Brown 1 ; Christophe Fraser 2 On behalf of the Pangea_HIV Consortium 1 University of Edinburgh, Edinburgh, United Kingdom; 2 Imperial College London, London, United Kingdom; 3 University of Glasgow, Glasgow, United Kingdom Background: PANGEA_HIV (Phylogenetics and Networks for Generalised HIV Epidemics in Africa) will generate a large volume of next generation viral sequence data from generalized HIV epidemics in sub-Saharan Africa in order to better characterize these epidemics and evaluate HIV prevention efforts. However, the accuracy and reliability of phylogenetic tools to measure aspects of transmission dynamics in these settings is not known. Methods: The PANGEA_HIV methodology working group conducted a methods comparison exercise in collaboration with multiple, independent research groups to identify the accuracy and power of phylogenetic methods in estimating recent changes in HIV incidence. Two, highly detailed, agent-based epidemiological models capturing generalized HIV transmission dynamics in a village-like, and regional population were developed. Simulated subtype C phylogenies were generated from the transmission tree output which was selected to represent populations varying in HIV incidence dynamics, population size, sampling fraction and model assumptions. Sample datasets of up to several hundred sequences of gag, pol and env for each individual sampled have been generated. These will be coded before distribution to participating collaborators. Results: First analyses of simple simulated datasets have been performed on pol sequences using a recently developed automated tool (“CPT”) which identifies sequence clusters at a maximum genetic distance of 4.5% and bootstrap support of 90%. The samples analysed came from the village model sampled in growth phase (~25 yr post introduction, 4% incidence) and decline (3 yrs after introduction of ART, 2% incidence), with a 20% sampling density. The CPT detected a highly significant decrease in mean cluster size (from 4.13 to 2.76, p = 0.002) and an increase in normalised cluster maximum genetic distance (0.0076 to 0.011, p < 1 x 10e-4), along with a highly significant increase overall in branch lengths (Fig 1).

Poster Abstracts

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CROI 2015