Abstract

Treatment as Prevention (TasP) using directly-acting antivirals has been advocated for Hepatitis C Virus (HCV) in people who inject drugs (PWID), but treatment is expensive and TasP’s effectiveness is uncertain. Previous modelling has assumed a homogeneously-mixed population or a static network lacking turnover in the population and injecting partnerships. We developed a transmission-dynamic model on a dynamic network of injecting partnerships using data from survey of injecting behaviour carried out in London, UK. We studied transmission on a novel exponential-clustered network, as well as on two simpler networks for comparison, an exponential unclustered and a random network, and found that TasP’s effectiveness differs markedly. With respect to an exponential-clustered network, the random network (and homogeneously-mixed population) overestimate TasP’s effectiveness, whereas the exponential-unclustered network underestimates it. For all network types TasP’s effectiveness depends on whether treated patients change risk behaviour, and on treatment coverage: higher coverage requires fewer total treatments for the same health gain. Whilst TasP can greatly reduce HCV prevalence, incidence of infection, and incidence of reinfection in PWID, assessment of TasP’s effectiveness needs to take account of the injecting-partnership network structure and post-treatment behaviour change, and further empirical study is required.

Highlights

  • Hepatitis C Virus (HCV) infection among people who inject drugs (PWID) is a public health priority, with prevalence in London being around 43%.[Aldridge et al submitted] With the advent of direct-acting antivirals (DAAs), which are more tolerable and have higher efficacy than previous therapy, with cure rates up to 90%1, Treatment as Prevention (TasP) for HCV in PWID has received attention[2,3,4,5]

  • This paper focuses on the stationary state

  • To our knowledge we present the first dynamic network model for the study of TasP of HCV

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Summary

Introduction

Hepatitis C Virus (HCV) infection among people who inject drugs (PWID) is a public health priority, with prevalence in London being around 43%.[Aldridge et al submitted] With the advent of direct-acting antivirals (DAAs), which are more tolerable and have higher efficacy than previous therapy, with cure rates up to 90%1, Treatment as Prevention (TasP) for HCV in PWID has received attention[2,3,4,5]. It remains difficult to infer to the structure of the full network, as respondent-driven sampling generally overestimates small loops[10], and often questionnaires have limited the maximum number of injecting partners that could be reported, so truncating the reported frequency distribution[9, 11]. These networks models are all static and so do not incorporate entry into and exit from the network of PWID, or changes over time in individuals’ injecting partners, which will be important for transmission dynamics since they occur on a similar timescale to the duration of infection[12]. The magnitude of this population-level effect is expected to depend upon network structure and rates of treatment in the population, which we explore

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