Assessment of the dose-response relationship of Campylobacter jejuni

Int J Food Microbiol. 1996 Jun;30(1-2):101-11. doi: 10.1016/0168-1605(96)00994-4.


Mathematical relations describing the risk of infection after exposure to enteropathogens are important tools for the evaluation of the potential health risk from exposure via food and water. A quantitative description of the dose-response relation for Campylobacter jejuni with the Beta-Poisson model was fitted to experimental data of infection with Campylobacter jejuni (as determined by shedding of C. jejuni) obtained in human feeding studies performed by Black et al. (1988). The maximum likelihood estimates for the Beta-Poisson model parameters based on these data are: alpha = 0.145 and beta = 7.59. The fit of the model on the experimental data was good: the difference between the likelihood obtained with the Beta-Poisson model and the maximum possible likelihood was not significant. The occurrence of symptoms of intestinal illness did not follow a similar dose-related trend. Overall, 22% of the infected volunteers developed symptoms (diarrhea, fever). The highest illness-to-infection ratio was found at an intermediate dose (9 x 10(4)). The dose-response relation and the illness-to-infection ratio appeared to differ between different C. jejuni isolates. The dose-response relation derived from feeding studies with a single isolate should therefore be considered indicative. The absence of experimental data in the low dose range resulted in a relatively large confidence interval at low doses. However, in cases where the dose-response relation has been applied so far to estimate the health risk of exposure to C. jejuni in water, the uncertainty in the dose-response relation was insignificant compared to the uncertainty in the exposure estimate.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Campylobacter Infections / epidemiology*
  • Campylobacter Infections / microbiology
  • Campylobacter jejuni*
  • Food Microbiology*
  • Humans
  • Poisson Distribution
  • Risk Assessment
  • Water Microbiology*