A6 Using phylodynamic modelling to estimate the population attributable fraction of HIV spread due to key populations in Dakar, Senegal

Although it has long been believed that certain key populations contribute disproportionately to HIV infection, the proportion of transmission events attributable to them is poorly understood. Most existing methods for estimating the population attributable fraction (PAF) are derived from the proportion of prevalent infections found in each group, or from static modes of transmission studies. Although these methods are useful in obtaining a cross-sectional estimate of the fraction of incident infections acquired in each group, they do not take into account the chain of transmission, and thus may underestimate the contribution of key populations. Using a transmission dynamics model, we aim to estimate the PAF of female sex workers, clients, and men who have sex with men to the HIV epidemic of Dakar, Senegal. On top of behavioural and epidemiological data, we will have access to genetic data from these key populations from an ongoing study, as well as historical samples from the Los Alamos database. As genetic diversity is shaped by epidemiological history, population genetic modelling of our sequence data can be informative about epidemic size and the migration of lineages through space and between risk groups. Our model will be first parameterised and fitted to behavioural and epidemiological data. We will then perform a phylogenetic analysis on our sequence data, using known dates of sampling and a molecular clock model of sequence evolution. Using structured coalescent models, we can look at the balance of phylogenies and infer patterns of transmission (although we will not have a large enough sample to determine clusters). We can then refit the transmission model to the sequence data as well, and provide new estimates of the PAFs. The comparison of PAFs estimated with or without using sequence data will provide an insight into the added value of phylodynamic modelling, and may help reassess the role of key populations in this setting.