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Can antiviral therapy for HCV be a prevention tool for active IDUs? A modelling analysis
Peter Vickerman, Senior Lecturer of Mathematical Epidemiology, London School of Hygiene and Tropical Medicine
Abstract
Background:
The prevalence of hepatitis C (HCV) is
generally high amongst injecting drug user (IDU) populations in the
UK. Although evidence suggests HCV prevalence may have decreased in UK
since early 1990s, recent evidence suggests these declines have not
continued. This suggests that increased efforts with existing
prevention strategies or new strategies are needed to further reduce
the transmission of HCV amongst IDUs. HCV antiviral treatment is
effective for individual patients, including active IDUs, but few
active IDUs are currently treated. This analysis estimates the
possible impact of increasing coverage of existing interventions
(syringe distribution and opioid substitution therapy) and considers
the utility of HCV antiviral treatment as a possible new strategy for primary prevention of hepatitis C.
Methods:
An existing HCV transmission model was used to estimate the
impact of increased coverage of syringe distribution and opioid
substitution therapy. A novel hepatitis C transmission model was
developed to estimate the impact of HCV antiviral treatment (62.5%
average sustained viral response - SVR) in setting with different
levels of baseline HCV infection. The model assumed no retreatment
after initial treatment failure, potential re-infection for those cured, and no HCV immunity.
Scenarios with varied treatment response rates, immunity, or
retreatment of treatment failures were explored.
Results:
Increasing the coverage of syringe distribution and opioid
substitution therapy will reduce HCV transmission but are unlikely to
reduce it to low levels. In contrast, for an IDU population with 20%
baseline chronic prevalence, increasing the treatment rate of active
IDUs to 5 or 10 HCV infections per 1000 IDUs per year could result in
a 15% and 30% reduction in chronic prevalence after 10 years,
respectively. These reductions in prevalence are nearly doubled after
20 years but are almost halved if baseline prevalence is 40% and
quartered if baseline prevalence is 60%. Sensitivity analyses show
that: the prevalence reductions remain even if the HCV cure rate (SVR)
is assumed to be 25% lower among active IDU than current evidence
suggests; and retreatment of treatment failures does not alter the
short-term.
Conclusions:
Additional strategies are needed to control the
transmission of HCV amongst injecting drug users. Despite the
possibility of re-infection, modest rates of hepatitis C treatment
amongst active injecting drug users could effectively reduce
transmission. It is essential that strategies to treat hepatitis C
among active injectors are evaluated to explore whether it could be a tool to aid prevention.
TOP
Biography
Peter Vickerman is a senior modeller for the HIVTools
Research Group and the Centre for Research on Drugs and Health
Behaviour at the London School of Hygiene and Tropical Medicine. He is
also an honorary researcher at the University of Bristol. He has been
modelling the transmission of HIV and sexually transmitted infections
(STIs) for eleven years, and infectious diseases for 15 years. He has
published over 40 articles in peer reviewed journals. Originally
trained as a mathematician, with a D.Phil in mathematical epidemiology
of Leishmaniasis, his research focuses on the use of mathematical
modelling with detailed data to help understand and explore the
transmission of different infectious diseases and the impact and cost-effectiveness of varied prevention measures.
Specific expertise focuses on modelling the transmission of HIV and
other STIs amongst different risk groups and blood borne viruses
transmitted between injecting drug users. His research interests include modelling the joint transmission and interaction of different
infections (e.g. transmission of HIV and Hepatitis C amongst injecting
drug users) in different settings and exploring how characteristics of
epidemics can affect the impact of different interventions.
Methodological areas of interest include: understanding the
implications of behavioural and biological data uncertainty on model
impact and cost-effectiveness projections; and trying to understand
and accurately estimate how new interventions could affect the
subsequent transmission of different infections. He has extensive
experience of conducting collaborative research with organisations in
Asia, Africa and Eastern Europe, and is the PI or co-PI on a numerous modelling projects.
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