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dc.contributor.authorHellard, M.
dc.contributor.authorRolls, D.
dc.contributor.authorSacks-Davis, R.
dc.contributor.authorRobins, G.
dc.contributor.authorPattison, P.
dc.contributor.authorHiggs, Peter
dc.contributor.authorAitken, C.
dc.contributor.authorMcBryde, E.
dc.date.accessioned2017-01-30T11:31:37Z
dc.date.available2017-01-30T11:31:37Z
dc.date.created2014-10-14T00:55:08Z
dc.date.issued2014
dc.identifier.citationHellard, M. and Rolls, D. and Sacks-Davis, R. and Robins, G. and Pattison, P. and Higgs, P. and Aitken, C. et al. 2014. The impact of injecting networks on hepatitis C transmission and treatment in people who inject drugs. Hepatology. 60 (6): pp. 1861-1870.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/12592
dc.identifier.doi10.1002/hep.27403
dc.description.abstract

With the development of new highly efficacious direct acting antiviral treatments (DAAs) for hepatitis C (HCV), the concept of treatment as prevention is gaining credence. To date the majority of mathematical models assume perfect mixing with injectors having equal contact with all other injectors. This paper explores how using a networks based approach to treat people who inject drugs (PWID) with DAAs affects HCV prevalence. Method: Using observational data we parameterized an Exponential Random Graph Model containing 524 nodes. We simulated transmission of HCV through this network using a discrete time, stochastic transmission model. The effect of five treatment strategies on the prevalence of HCV was investigated; two of these strategies were 1) treat randomly selected nodes and 2) “treat your friends” where an individual is chosen at random for treatment and all their infected neighbours are treated. Results: As treatment coverage increases, HCV prevalence at 10 years reduces for both the high efficacy and low efficacy treatment. Within each set of parameters, the “treat your friends” strategy performed better than the random strategy being most marked for higher efficacy treatment. For example over 10 years of treating 25 per 1000 PWID, the prevalence drops from 50% to 40% for the random strategy, and to 33% for the “treat your friends” strategy (6.5% difference, 95% CI 5.1 – 8.1%). Discussion: “Treat your friends” is a feasible means of utilising network strategies to improve treatment efficiency. In an era of highly efficacious and highly tolerable treatment such an approach will benefit not just the individual but the community more broadly by reducing the prevalence of HCV amongst PWID.

dc.publisherJohn Wiley & Sons Inc.
dc.titleThe impact of injecting networks on hepatitis C transmission and treatment in people who inject drugs
dc.typeJournal Article
dcterms.source.volume*
dcterms.source.startPage*
dcterms.source.endPage*
dcterms.source.issn0270-9139
dcterms.source.titleHepatology
curtin.note

This is the accepted version of the following article: Hellard, M. and Rolls, D. and Sacks-Davis, R. and Robins, G. and Pattison, P. and Higgs, P. and Aitken, C. et al. 2014. The impact of injecting networks on hepatitis C transmission and treatment in people who inject drugs. Hepatology. 60 (6): pp. 1861-1870, which has been published in final form at http://doi.org/10.1002/hep.27403

curtin.departmentNational Drug Research Institute (Research Institute)
curtin.accessStatusOpen access


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