title: Attribution of foodborne pathogens using structured expert elicitation.
abstract: OBJECTIVE
  To estimate the fraction of human cases of enterically transmitted illness by five major pathways (food, environment, direct animal contact, human-human transmission, and travel) and by 11 groups within the food pathway.
  
  
  METHODS
  Food safety experts were asked to provide their estimates of the most likely range for each of the parameters. Joint probability distributions were created by probabilistic inversion (PI).
  
  
  RESULTS
  Sixteen experts participated in the study. PI resulted in good fits for most pathogens. Qualitatively, expert estimates were similar to earlier published studies but the estimated fraction of foodborne transmission was lower for most pathogens. Biologically less plausible pathways were given some weight by the experts. Uncertainties were smallest for pathogens with dominant transmission routes.
  
  
  CONCLUSIONS
  Structured expert studies are a feasible method for source attribution, but methods need further development.
  
  
  CONCLUSIONS
  These estimates can be combined with data on incidence, disease burden and costs to provide specific estimates of the public health impact of foodborne illness, and to identify the food groups that have the highest impact.
authors.affiliation: Laboratory for Zoonoses and Environmental Microbiology, Centre for Infectious Disease Control Netherlands, National Institute for Public Health and the Environment, Bilthoven, The Netherlands. arie.havelaar@rivm.nl
authors.forename: Arie H
authors.initials: AH
authors.lastname: Havelaar
authors.forename: Angela Vargas
authors.initials: AV
authors.lastname: Galindo
authors.forename: Dorotha
authors.initials: D
authors.lastname: Kurowicka
authors.forename: Roger M
authors.initials: RM
authors.lastname: Cooke
mesh_terms: D000818:Animals; D004196:Disease Outbreaks; D018562:Disease Transmission, Infectious; D005516:Food Microbiology; D005517:Foodborne Diseases / Q000453:epidemiology*; D006801:Humans; D015994:Incidence; D011634:Public Health / Q000639:trends*