A latent class approach to identify multi-risk profiles associated with phylogenetic clustering of recent hepatitis C virus infection in Australia and New Zealand from 2004 to 2015

Introduction: Over the last two decades, the incidence of hepatitis C virus (HCV) co-infection among men who have sex with men (MSM) living with HIV began increasing in post-industrialized countries. Little is known about transmission of acute or recent HCV, in particular among MSM living with HIV co-infection, which creates uncertainty about potential for reinfection after HCV treatment. Using phylogenetic methods, clinical, epidemiological and molecular data can be combined to better understand transmission patterns. These insights may help identify strategies to reduce reinfection risk, enhancing effectiveness of HCV treatment as prevention strategies. The aim of this study was to identify multi-risk profiles and factors associated with phylogenetic pairs and clusters among people with recent HCV infection. Methods: Data and specimens from five studies of recent HCV in Australia and New Zealand (2004 to 2015) were used. HCV Core-E2 sequences were used to infer maximum likelihood trees. Clusters were identified using 90% bootstrap and 5% genetic distance threshold. Multivariate logistic regression and latent class analyses were performed. Results: Among 237 participants with Core-E2 sequences, 47% were in a pair/cluster. Among HIV/HCV co-infected participants, 60% (74/123) were in a pair/cluster, compared to 30% (34/114) with HCV mono-infection (p < 0.001). HIV/HCV co-infection (vs. HCV mono-infection; adjusted odds ratio (AOR), 2.37, 95% confidence interval (CI), 1.45, 5.15) was independently associated with phylogenetic clustering. Latent class analysis identified three distinct risk profiles: (1) people who inject drugs, (2) HIV-positive gay and bisexual men (GBM) with low probability of injecting drug use (IDU) and (3) GBM with IDU & sexual risk behaviour. Class 2 (vs. Class 1, AOR 3.40; 95% CI, 1.52, 7.60), was independently associated with phylogenetic clustering. Many clusters displayed homogeneous characteristics, such as containing individuals exclusively from one city, individuals all with HIV/HCV co-infection or individuals sharing the same route of acquisition of HCV. Conclusions: Clusters containing individuals with specific characteristics suggest that HCV transmission occurs through discrete networks, particularly among HIV/HCV co-infected individuals. The greater proportion of clustering found among HIV/HCV co-infected participants highlights the need to provide broad direct-acting antiviral access encouraging rapid uptake in this population and ongoing monitoring of the phylogeny.