Hepatitis C transmission and treatment as prevention - The role of the injecting network

Background: The hepatitis C virus (HCV) epidemic is a major health issue; in most developed countries it is driven by people who inject drugs (PWID). Injecting networks powerfully influence HCV transmission. In this paper we provide an overview of 10 years of research into injecting networks and HCV...

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Main Authors: Hellard, M., McBryde, E., Sacks Davis, R., Rolls, D., Higgs, Peter, Aitken, C., Thompson, A., Doyle, J., Pattison, P., Robins, G.
Format: Journal Article
Published: Elsevier 2015
Online Access:http://hdl.handle.net/20.500.11937/36231
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author Hellard, M.
McBryde, E.
Sacks Davis, R.
Rolls, D.
Higgs, Peter
Aitken, C.
Thompson, A.
Doyle, J.
Pattison, P.
Robins, G.
author_facet Hellard, M.
McBryde, E.
Sacks Davis, R.
Rolls, D.
Higgs, Peter
Aitken, C.
Thompson, A.
Doyle, J.
Pattison, P.
Robins, G.
author_sort Hellard, M.
building Curtin Institutional Repository
collection Online Access
description Background: The hepatitis C virus (HCV) epidemic is a major health issue; in most developed countries it is driven by people who inject drugs (PWID). Injecting networks powerfully influence HCV transmission. In this paper we provide an overview of 10 years of research into injecting networks and HCV, culminating in a network-based approach to provision of direct-acting antiviral therapy. Methods: Between 2005 and 2010 we followed a cohort of 413 PWID, measuring HCV incidence, prevalence and injecting risk, including network-related factors. We developed an individual-based HCV transmission model, using it to simulate the spread of HCV through the empirical social network of PWID. In addition, we created an empirically grounded network model of injecting relationships using exponential random graph models (ERGMs), allowing simulation of realistic networks for investigating HCV treatment and intervention strategies. Our empirical work and modelling underpins the TAP Study, which is examining the feasibility of community-based treatment of PWID with DAAs. Results: We observed incidence rates of HCV primary infection and reinfection of 12.8 per 100 person-years (PY) (95%CI: 7.7-20.0) and 28.8 per 100 PY (95%CI: 15.0-55.4), respectively, and determined that HCV transmission clusters correlated with reported injecting relationships. Transmission modelling showed that the empirical network provided some protective effect, slowing HCV transmission compared to a fully connected, homogenous PWID population. Our ERGMs revealed that treating PWID and all their contacts was the most effective strategy and targeting treatment to infected PWID with the most contacts the least effective. Conclusion: Networks-based approaches greatly increase understanding of HCV transmission and will inform the implementation of treatment as prevention using DAAs.
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institution Curtin University Malaysia
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spelling curtin-20.500.11937-362312017-09-13T15:18:38Z Hepatitis C transmission and treatment as prevention - The role of the injecting network Hellard, M. McBryde, E. Sacks Davis, R. Rolls, D. Higgs, Peter Aitken, C. Thompson, A. Doyle, J. Pattison, P. Robins, G. Background: The hepatitis C virus (HCV) epidemic is a major health issue; in most developed countries it is driven by people who inject drugs (PWID). Injecting networks powerfully influence HCV transmission. In this paper we provide an overview of 10 years of research into injecting networks and HCV, culminating in a network-based approach to provision of direct-acting antiviral therapy. Methods: Between 2005 and 2010 we followed a cohort of 413 PWID, measuring HCV incidence, prevalence and injecting risk, including network-related factors. We developed an individual-based HCV transmission model, using it to simulate the spread of HCV through the empirical social network of PWID. In addition, we created an empirically grounded network model of injecting relationships using exponential random graph models (ERGMs), allowing simulation of realistic networks for investigating HCV treatment and intervention strategies. Our empirical work and modelling underpins the TAP Study, which is examining the feasibility of community-based treatment of PWID with DAAs. Results: We observed incidence rates of HCV primary infection and reinfection of 12.8 per 100 person-years (PY) (95%CI: 7.7-20.0) and 28.8 per 100 PY (95%CI: 15.0-55.4), respectively, and determined that HCV transmission clusters correlated with reported injecting relationships. Transmission modelling showed that the empirical network provided some protective effect, slowing HCV transmission compared to a fully connected, homogenous PWID population. Our ERGMs revealed that treating PWID and all their contacts was the most effective strategy and targeting treatment to infected PWID with the most contacts the least effective. Conclusion: Networks-based approaches greatly increase understanding of HCV transmission and will inform the implementation of treatment as prevention using DAAs. 2015 Journal Article http://hdl.handle.net/20.500.11937/36231 10.1016/j.drugpo.2015.05.006 Elsevier fulltext
spellingShingle Hellard, M.
McBryde, E.
Sacks Davis, R.
Rolls, D.
Higgs, Peter
Aitken, C.
Thompson, A.
Doyle, J.
Pattison, P.
Robins, G.
Hepatitis C transmission and treatment as prevention - The role of the injecting network
title Hepatitis C transmission and treatment as prevention - The role of the injecting network
title_full Hepatitis C transmission and treatment as prevention - The role of the injecting network
title_fullStr Hepatitis C transmission and treatment as prevention - The role of the injecting network
title_full_unstemmed Hepatitis C transmission and treatment as prevention - The role of the injecting network
title_short Hepatitis C transmission and treatment as prevention - The role of the injecting network
title_sort hepatitis c transmission and treatment as prevention - the role of the injecting network
url http://hdl.handle.net/20.500.11937/36231