Applied Math Mathematical Biology Seminar | William Wong, Using mathematical modelling to inform health policy decision making in hepatitis C

MC 6460

Speaker

William Wong, School of Pharmacy, University of Waterloo

Title

Using mathematical modelling to inform health policy decision making in hepatitis C

Abstract

Hepatitis C health policy decision-making on prevention and treatment is complex. Preventive interventions such as syringe distribution programs can prevent forward transmission. Screening coupled with treatment is effective in reducing disease burden for hepatitis C virus (HCV) infections, which are asymptomatic until later stages of the disease. Drugs currently approved for HCV treatment are effective but costly. For HCV, where benefits of screening and treatment occur decades into the future, mathematical modeling is the only practical option for policy makers to analyze the impact of prevention and treatment.

In this talk, I present three studies that we had used mathematical modeling to generate evidence to inform HCV-related health polices: 1) A state-transition model that evaluate the cost-effectiveness of HCV-related screening and treatment interventions; 2) A back-calculation model based on a Bayesian MCMC algorithm to estimate chronic hepatitis C prevalence and undiagnosed proportion; and 3) An agent-based model that track hepatitis C elimination in an ongoing pandemic era.