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A model-based framework for chronic hepatitis C prevalence estimation.

Abdullah HamadehZeny FengMurray KrahnWilliam W L Wong
Published in: PloS one (2019)
Chronic hepatitis C (CHC) continues to be a highly burdensome disease worldwide. The often-asymptomatic nature of early-stage CHC means that the disease often remains undiagnosed, leaving its prevalence highly uncertain. This generates significant uncertainty in the planning of hepatitis C eradication programs to meet WHO targets. The aim of this work is to establish a mathematical framework for the estimation of a geographic locale's CHC prevalence and the proportion of its CHC population that remains undiagnosed. A Bayesian MCMC approach is taken to infer these populations from the observed occurrence of CHC-related events using a recently published natural history model of the disease. Using the Canadian context as a specific example, this study estimates that in 2013, the CHC prevalence rate in Canada was 0.63% (95% CI: 0.53% - 0.72%), with 27.1% (95% CI: 19.3% - 36.1%) of the infected population undiagnosed.
Keyphrases
  • risk factors
  • early stage
  • risk assessment
  • public health
  • randomized controlled trial
  • systematic review
  • neoadjuvant chemotherapy
  • locally advanced