title: Quantifying Parameter and Structural Uncertainty of Dynamic Disease Transmission Models Using MCMC: An Application to Rotavirus Vaccination in England and Wales.
abstract: Two vaccines (Rotarix and RotaTeq) are highly effective at preventing severe rotavirus disease. Rotavirus vaccination has been introduced in the United Kingdom and other countries partly based on modeling and cost-effectiveness results. However, most of these models fail to account for the uncertainty about several vaccine characteristics and the mechanism of vaccine action.
  
  
  
  A deterministic dynamic transmission model of rotavirus vaccination in the United Kingdom was developed. This improves on previous models by 1) allowing for 2 different mechanisms of action for Rotarix and RotaTeq, 2) using clinical trial data to understand these mechanisms, and 3) accounting for uncertainty by using Markov Chain Monte Carlo.
  
  
  
  In the long run, Rotarix and RotaTeq are predicted to reduce the overall rotavirus incidence by 50% (39%-63%) and 44% (30%-62%), respectively but with an increase in incidence in primary school children and adults up to 25 y of age. The vaccines are estimated to give more protection than 1 or 2 natural infections. The duration of protection is highly uncertain but has only impact on the predicted reduction in rotavirus burden for values lower than 10 y. The 2 vaccine mechanism structures fit equally well with the clinical trial data. Long-term postvaccination dynamics cannot be predicted reliably with the data available.
  
  
  
  Accounting for the joint uncertainty of several vaccine characteristics resulted in more insight into which of these are crucial for determining the impact of rotavirus vaccination. Data for up to at least 10 y postvaccination and covering older children and adults are crucial to address remaining questions on the impact of widespread rotavirus vaccination.
authors.affiliation: Centre for Health Economics Research & Modeling of Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium (JB, LW)|Department of Infectious Diseases Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK (JB, HJ, WJE, MJ)
authors.forename: Joke
authors.initials: J
authors.lastname: Bilcke
authors.affiliation: Modelling and Economics Unit, Public Health England, London, UK (RC, MJ)
authors.forename: Ruth
authors.initials: R
authors.lastname: Chapman
authors.affiliation: Department of Primary Care and Public Health, School of Public Health, Imperial College, London, UK (CA)
authors.forename: Christina
authors.initials: C
authors.lastname: Atchison
authors.affiliation: Complex Systems in Biology Group, Centre for Vascular Research, UNSW Australia, Sydney, New South Wales, Australia (DC)
authors.forename: Deborah
authors.initials: D
authors.lastname: Cromer
authors.affiliation: Department of Infectious Diseases Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK (JB, HJ, WJE, MJ)
authors.forename: Helen
authors.initials: H
authors.lastname: Johnson
authors.affiliation: Centre for Health Economics Research & Modeling of Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute (VAXINFECTIO), University of Antwerp, Antwerp, Belgium (JB, LW)|Department of Mathematics and Computer Science, University of Antwerp, Antwerp, Belgium (LW)|Interuniversity Institute for Biostatistics and Statistical Bioinformatics, Hasselt University, Diepenbeek, Belgium (LW)
authors.forename: Lander
authors.initials: L
authors.lastname: Willem
authors.affiliation: Department of Applied Sciences and Health, Coventry University, Coventry, UK (MC)
authors.forename: Martin
authors.initials: M
authors.lastname: Cox
authors.affiliation: Department of Infectious Diseases Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK (JB, HJ, WJE, MJ)
authors.forename: William John
authors.initials: WJ
authors.lastname: Edmunds
authors.affiliation: Department of Infectious Diseases Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK (JB, HJ, WJE, MJ)|Modelling and Economics Unit, Public Health England, London, UK (RC, MJ)
authors.forename: Mark
authors.initials: M
authors.lastname: Jit
mesh_terms: D000293:Adolescent; D000328:Adult; D002648:Child; D002675:Child, Preschool; D003362:Cost-Benefit Analysis; D004739:England / Q000453:epidemiology; D006801:Humans; D007223:Infant; D008390:Markov Chains; D008954:Models, Biological; D012401:Rotavirus / Q000276:immunology; D012400:Rotavirus Infections / Q000453:epidemiology / Q000517:prevention & control / Q000635:transmission; D022243:Rotavirus Vaccines / Q000627:therapeutic use*; D035501:Uncertainty; D014613:Vaccines, Attenuated; D014852:Wales / Q000453:epidemiology; D055815:Young Adult
chemical_list: C492535:RotaTeq; D022243:Rotavirus Vaccines; D014613:Vaccines, Attenuated
keywords: Markov Chain Monte Carlo; dynamic transmission model; rotavirus; uncertainty; vaccination