OBJECTIVES: To develop a mathematical model to project the potential impact of hepatitis C virus (HCV) treatment on HCV infection prevalence among people who inject drugs (PWID). DESIGN AND SETTING: An existing model of HCV transmission among PWID was parameterised using data from Victoria, Australia, including specific parameter estimates of the number of people who are currently active injecting drug users, average duration of injecting, chronic HCV infection prevalence among PWID, annual mortality, and annual HCV treatment rate. We also explored the impact of prevalence uncertainty, program scale-up, and new treatments. MAIN OUTCOME MEASURE: Prevalence of chronic HCV infection among people who are currently active injecting drug users. RESULTS: With annual treatment rates of 13, 17, or 25 per 1000 PWID, the model predicts relative prevalence reductions of 20%, 30%, and 50%, respectively, within 30 years. If new treatments giving higher sustained viral response rates are available in 5 years, estimated impact is increased by 21%–23% at 15 years, and 17%–38% at 30 years, depending on treatment rates. CONCLUSIONS: This model suggests that modest rates of current HCV treatment among PWID in Victoria, Australia could halve HCV infection prevalence among PWID in 30 years. This finding suggests that interventions aimed at increasing access to HCV treatment in community clinics will benefit individual PWID and reduce HCV infection prevalence.
OBJECTIVES: To develop a mathematical model to project the potential impact of hepatitis C virus (HCV) treatment on HCV infection prevalence among people who inject drugs (PWID). DESIGN AND SETTING: An existing model of HCV transmission among PWID was parameterised using data from Victoria, Australia, including specific parameter estimates of the number of people who are currently active injecting drug users, average duration of injecting, chronic HCV infection prevalence among PWID, annual mortality, and annual HCV treatment rate. We also explored the impact of prevalence uncertainty, program scale-up, and new treatments. MAIN OUTCOME MEASURE: Prevalence of chronic HCV infection among people who are currently active injecting drug users. RESULTS: With annual treatment rates of 13, 17, or 25 per 1000 PWID, the model predicts relative prevalence reductions of 20%, 30%, and 50%, respectively, within 30 years. If new treatments giving higher sustained viral response rates are available in 5 years, estimated impact is increased by 21%–23% at 15 years, and 17%–38% at 30 years, depending on treatment rates. CONCLUSIONS: This model suggests that modest rates of current HCV treatment among PWID in Victoria, Australia could halve HCV infection prevalence among PWID in 30 years. This finding suggests that interventions aimed at increasing access to HCV treatment in community clinics will benefit individual PWID and reduce HCV infection prevalence.
Authors: Paul M Trembling; Sudeep Tanwar; William M Rosenberg; Geoffrey M Dusheiko Journal: Nat Rev Gastroenterol Hepatol Date: 2013-09-10 Impact factor: 46.802
Authors: Ivo Ditah; Badr Al Bawardy; Humberto C Gonzalez; Behnam Saberi; Callistus Ditah; Patrick S Kamath; Michael Charlton Journal: Am J Gastroenterol Date: 2015-03-10 Impact factor: 10.864
Authors: Joseph S Doyle; Esther Aspinall; Danny Liew; Alexander J Thompson; Margaret E Hellard Journal: Br J Clin Pharmacol Date: 2013-04 Impact factor: 4.335