title: Many hepatitis C reinfections that spontaneously clear may be undetected: Markov-chain Monte Carlo analysis of observational study data.
abstract: Hepatitis C virus (HCV) reinfection rates are probably underestimated due to reinfection episodes occurring between study visits. A Markov model of HCV reinfection and spontaneous clearance was fitted to empirical data. Bayesian post-estimation was used to project reinfection rates, reinfection spontaneous clearance probability and duration of reinfection. Uniform prior probability distributions were assumed for reinfection rate (more than 0), spontaneous clearance probability (0-1) and duration (0.25-6.00 months). Model estimates were 104 per 100 person-years (95% CrI: 21-344), 0.84 (95% CrI: 0.59-0.98) and 1.3 months (95% CrI: 0.3-4.1) for reinfection rate, spontaneous clearance probability and duration, respectively. Simulation studies were used to assess model validity, demonstrating that the Bayesian model estimates provided useful information about the possible sources and magnitude of bias in epidemiological estimates of reinfection rates, probability of reinfection clearance and duration or reinfection. The quality of the Bayesian estimates improved for larger samples and shorter test intervals. Uncertainty in model estimates notwithstanding, findings suggest that HCV reinfections frequently and quickly result in spontaneous clearance, with many reinfection events going unobserved.
authors.affiliation: Centre for Population Health, Burnet Institute, Melbourne, Australia Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia rachelsd@burnet.edu.au.
authors.forename: Rachel
authors.initials: R
authors.lastname: Sacks-Davis
authors.affiliation: Centre for Population Health, Burnet Institute, Melbourne, Australia Victorian Infectious Diseases Service, Royal Melbourne Hospital, Melbourne, Australia Department of Medicine, University of Melbourne, Melbourne, Australia.
authors.forename: Emma
authors.initials: E
authors.lastname: McBryde
authors.affiliation: The Kirby Institute, University of New South Wales, Sydney, Australia.
authors.forename: Jason
authors.initials: J
authors.lastname: Grebely
authors.affiliation: Centre for Population Health, Burnet Institute, Melbourne, Australia Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia.
authors.forename: Margaret
authors.initials: M
authors.lastname: Hellard
authors.affiliation: School of Social and Community Medicine, University of Bristol, Bristol, UK.
authors.forename: Peter
authors.initials: P
authors.lastname: Vickerman
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D003198:Computer Simulation; D016174:Hepacivirus; D006526:Hepatitis C / Q000175:diagnosis* / Q000628:therapy / Q000821:virology*; D006801:Humans; D008390:Markov Chains; D015233:Models, Statistical; D009010:Monte Carlo Method; D011336:Probability; D012367:RNA, Viral / Q000235:genetics; D012008:Recurrence; D015203:Reproducibility of Results; D013997:Time Factors; D016896:Treatment Outcome
chemical_list: D012367:RNA, Viral
keywords: Monte Carlo Markov chain; epidemiology; hepatitis C infection