Literature DB >> 26305706

Modeling hepatitis C virus transmission among people who inject drugs: Assumptions, limitations and future challenges.

Nick Scott1,2, Margaret Hellard1,2,3, Emma Sue McBryde1,4,5.   

Abstract

The discovery of highly effective hepatitis C virus (HCV) treatments has led to discussion of elimination and intensified interest in models of HCV transmission. In developed settings, HCV disproportionally affects people who inject drugs (PWID), and models are typically used to provide an evidence base for the effectiveness of interventions such as needle and syringe programs, opioid substitution therapy and more recently treating PWID with new generation therapies to achieve specified reductions in prevalence and / or incidence. This manuscript reviews deterministic compartmental S-I, deterministic compartmental S-I-S and network-based transmission models of HCV among PWID. We detail typical assumptions made when modeling injecting risk behavior, virus transmission, treatment and re-infection and how they correspond with available evidence and empirical data.

Entities:  

Keywords:  Hepatitis C virus; infectious disease; injecting drug use; mathematical models; transmission

Mesh:

Year:  2015        PMID: 26305706      PMCID: PMC4994822          DOI: 10.1080/21505594.2015.1085151

Source DB:  PubMed          Journal:  Virulence        ISSN: 2150-5594            Impact factor:   5.882


  77 in total

Review 1.  Global epidemiology of hepatitis B and hepatitis C in people who inject drugs: results of systematic reviews.

Authors:  Paul K Nelson; Bradley M Mathers; Benjamin Cowie; Holly Hagan; Don Des Jarlais; Danielle Horyniak; Louisa Degenhardt
Journal:  Lancet       Date:  2011-07-27       Impact factor: 79.321

2.  Hepatitis C virus treatment as prevention among injecting drug users: who should we cure first?

Authors:  Anneke S de Vos; Maria Prins; Mirjam E E Kretzschmar
Journal:  Addiction       Date:  2015-02-08       Impact factor: 6.526

3.  Mathematical modelling of hepatitis C treatment for injecting drug users.

Authors:  Natasha K Martin; Peter Vickerman; Matthew Hickman
Journal:  J Theor Biol       Date:  2011-01-12       Impact factor: 2.691

4.  Protection against persistence of hepatitis C.

Authors:  Shruti H Mehta; Andrea Cox; Donald R Hoover; Xiao-Hong Wang; Qing Mao; Stuart Ray; Steffanie A Strathdee; David Vlahov; David L Thomas
Journal:  Lancet       Date:  2002-04-27       Impact factor: 79.321

5.  The epidemic behavior of the hepatitis C virus.

Authors:  O G Pybus; M A Charleston; S Gupta; A Rambaut; E C Holmes; P H Harvey
Journal:  Science       Date:  2001-06-22       Impact factor: 47.728

6.  Hepatitis C virus vaccines in the era of new direct-acting antivirals.

Authors:  Chao Shi; Alexander Ploss
Journal:  Expert Rev Gastroenterol Hepatol       Date:  2013-02       Impact factor: 3.869

7.  Assessing the cost-effectiveness of treating chronic hepatitis C virus in people who inject drugs in Australia.

Authors:  Adam J Visconti; Joseph S Doyle; Amanda Weir; Alan M Shiell; Margaret E Hellard
Journal:  J Gastroenterol Hepatol       Date:  2013-04       Impact factor: 4.029

8.  The more you look, the more you find: effects of hepatitis C virus testing interval on reinfection incidence and clearance and implications for future vaccine study design.

Authors:  Peter Vickerman; Jason Grebely; Gregory J Dore; Rachel Sacks-Davis; Kimberly Page; David L Thomas; William O Osburn; Andrea L Cox; Campbell K Aitken; Matthew Hickman; Margaret Hellard
Journal:  J Infect Dis       Date:  2012-03-29       Impact factor: 5.226

9.  Combination interventions to prevent HCV transmission among people who inject drugs: modeling the impact of antiviral treatment, needle and syringe programs, and opiate substitution therapy.

Authors:  Natasha K Martin; Matthew Hickman; Sharon J Hutchinson; David J Goldberg; Peter Vickerman
Journal:  Clin Infect Dis       Date:  2013-08       Impact factor: 9.079

10.  The natural history of hepatitis C virus (HCV) infection.

Authors:  Stephen L Chen; Timothy R Morgan
Journal:  Int J Med Sci       Date:  2006-04-01       Impact factor: 3.738

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  7 in total

1.  Editorial: Mathematical modeling of infectious disease dynamics.

Authors:  Constantinos I Siettos
Journal:  Virulence       Date:  2016       Impact factor: 5.882

2.  The contribution of injection drug use to hepatitis C virus transmission globally, regionally, and at country level: a modelling study.

Authors:  Adam Trickey; Hannah Fraser; Aaron G Lim; Amy Peacock; Samantha Colledge; Josephine G Walker; Janni Leung; Jason Grebely; Sarah Larney; Natasha K Martin; Matthew Hickman; Louisa Degenhardt; Margaret T May; Peter Vickerman
Journal:  Lancet Gastroenterol Hepatol       Date:  2019-04-10

Review 3.  A review of network simulation models of hepatitis C virus and HIV among people who inject drugs.

Authors:  Meghan Bellerose; Lin Zhu; Liesl M Hagan; William W Thompson; Liisa M Randall; Yelena Malyuta; Joshua A Salomon; Benjamin P Linas
Journal:  Int J Drug Policy       Date:  2019-11-15

4.  Eliminating hepatitis C virus as a public health threat among HIV-positive men who have sex with men: a multi-modelling approach to understand differences in sexual risk behaviour.

Authors:  Nick Scott; Mark Stoové; David P Wilson; Olivia Keiser; Carol El-Hayek; Joseph Doyle; Margaret Hellard
Journal:  J Int AIDS Soc       Date:  2018-01       Impact factor: 5.396

5.  Structural Sensitivity in HIV Modeling: A Case Study of Vaccination.

Authors:  Cora L Bernard; Margaret L Brandeau
Journal:  Infect Dis Model       Date:  2017-11-11

6.  Injection drug network characteristics as a predictor of injection behaviour.

Authors:  Tim Spelman; Rachel Sacks-Davis; Paul Dietze; Peter Higgs; Margaret Hellard
Journal:  Epidemiol Infect       Date:  2019-01       Impact factor: 2.451

7.  Health outcomes and cost-effectiveness of diversion programs for low-level drug offenders: A model-based analysis.

Authors:  Cora L Bernard; Isabelle J Rao; Konner K Robison; Margaret L Brandeau
Journal:  PLoS Med       Date:  2020-10-13       Impact factor: 11.069

  7 in total

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