Eliminating hepatitis C among priority populations: dynamic transmission modeling studies to inform health policy

Background: Hepatitis C virus (HCV) spreads via unsterile injection materials, or, less efficiently, via sexual practices. Of 250,000 people living with HCV in Canada, 21,000 are coinfected with HIV, which exacerbates disease severity. The World Health Organization (WHO) targets for HCV elimination include reductions of incidence by 80% and mortality by 65% from 2015 to 2030. For Canada to meet these targets, a promising approach, known as micro-elimination, is to tailor elimination strategies to priority populations such as people who inject drugs (PWID), men who have sex with men (MSM), and those living with HIV (LWH). Evidence is needed to inform such locally relevant micro-elimination strategies.Objectives: My thesis’ aim was to identify strategies that can achieve and sustain HCV elimination in Montreal’s (Canada) priority groups. I first estimated temporal trends in, and factors associated with, HCV seroprevalence among MSM. Second, I assessed the potential of different interventions to achieve elimination among PWID by 2030. Third, I investigated post-elimination dynamics of HCV transmission among PWID under various scenarios.Methods: To obtain representative estimates of HCV seroprevalence and its associated factors among MSM, I standardised data from 2005 and 2008 surveys of Montreal MSM to 2018 data collected via respondent-driven sampling. The results informed my modelling work, which focused on HCV transmission via injection drug use (IDU). To assess direct and indirect effects of interventions among Montreal PWID, I developed a dynamic model of HIV-HCV coinfection calibrated to 16 years of surveillance data. I simulated increases in HCV testing, treatment, and coverage of opioid agonist therapy (OAT) and needle and syringe programs (NSP) from 2022 to 2030, varying priority groups (PWID LWH/all PWID; active/ex-injectors). I then assessed the sustainability of HCV elimination targets among PWID by modelling post-elimination scenarios (2030-2050) scaling down or suspending different combinations of these interventions.Results: Standardised HCV seroprevalence among MSM remained stable at 8% from 2005 to 2018 and was associated with past IDU and not with sexual behaviours. In my calibrated model, current intervention levels did not achieve elimination among PWID. Increasing testing or OAT and NSP alone made little difference. Reducing time from hepatitis C diagnosis to treatment initiation to 1 year for all PWID led to 95% and 99% reductions in HCV incidence and mortality, respectively, from 2022 to 2030. Post elimination, when scaling down all interventions to current levels, HCV incidence rebounded, doubling from 2 to 4 per 100 PY from 2030 to 2050. High-coverage NSP and OAT were key to either sustain elimination when scaling down testing and treatment or mitigate HCV resurgence when suspending testing and treatment.Discussion: HCV seroprevalence was high and associated with past IDU among Montreal MSM, showing the need to reduce HCV transmission via IDU in Montreal’s priority populations. In a setting with relatively high diagnosis and harm reduction coverage, scaling up treatment is the key to HCV micro-elimination among PWID, and its sustainability relies on access to NSP and OAT. Interventions should reach all PWID, regardless of HIV status or whether people have ceased injecting. Inherent study limitations include challenges in obtaining representative samples of hard-to-reach populations and unaccounted heterogeneity in the modelled population. Strengths include detailed analyses of a wealth of bio-behavioural survey data and the use of a calibrated coinfection model.Conclusions: HCV care and prevention needs overlap between priority populations and reducing transmission via IDU is key in Montreal. For PWID, HCV micro-elimination is contingent on scaling up treatment uptake for all, and high-coverage harm reduction can ensure that elimination efforts are sustained and provide long-term benefits

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