A molecular transmission network of recent hepatitis C infection in people with and without HIV: Implications for targeted treatment strategies.

Combining phylogenetic and network methodologies has the potential to better inform targeted interventions to prevent and treat infectious diseases. This study reconstructed a molecular transmission network for people with recent hepatitis C virus ( HCV) infection and modelled the impact of targeting directly acting antiviral ( DAA) treatment for HCV in the network. Participants were selected from three Australian studies of recent HCV from 2004 to 2014. HCV sequence data (Core-E2) from participants at the time of recent HCV detection were analysed to infer a network by connecting pairs of sequences whose divergence was ≤.03 substitutions/site. Logistic regression was used to identify factors associated with connectivity. Impact of targeting HCV DAAs at both HIV co-infected and random nodes was simulated (1 million replicates). Among 236 participants, 21% (n=49) were connected in the network. HCV/ HIV co-infected participants (47%) were more likely to be connected compared to HCV mono-infected participants (16%) ( OR 4.56; 95% CI; 2.13-9.74). Simulations targeting DAA HCV treatment to HCV/ HIV co-infected individuals prevented 2.5 times more onward infections than providing DAAs to randomly selected individuals. Results demonstrate that genetic distance-based network analyses can be used to identify characteristics associated with HCV transmission, informing targeted prevention and treatment strategies. [ABSTRACT FROM AUTHOR]