If you are experiencing problems downloading PDF or HTML fulltext, our helpdesk recommend clearing your browser cache and trying again. If you need help in clearing your cache, please click here . Still need help? Email help@ingentaconnect.com

Topics in Dose-Response Modeling

$37.00 plus tax (Refund Policy)

Buy Article:


Great uncertainty exists in conducting dose-response assessment for microbial pathogens. The data to support quantitative modeling of dose-response relationships are meager. Our philosophy in developing methodology to conduct microbial risk assessments has been to rely on data analysis and formal inferencing from the available data in constructing dose-response and exposure models. The probability of illness is a complex function of factors associated with the disease triangle: the host, the pathogen, and the environment including the food vehicle and indigenous microbial competitors. The epidemiological triangle and interactions between the components of the triangle are used to illustrate key issues in dose-response modeling that impact the estimation of risk and attendant uncertainty. Distinguishing between uncertainty (what is unknown) and variability (heterogeneity) is crucial in risk assessment. Uncertainty includes components that are associated with (i) parameter estimation for a given assumed model, and (ii) the unknown "true" model form among many plausible alternatives such as the exponential, Beta-Poisson, probit, logistic, and Gompertz. Uncertainty may be grossly understated if plausible alternative models are not tested in the analysis. Examples are presented of the impact of variability and uncertainty on species, strain, or serotype of microbial pathogens; variability in human response to administered doses of pathogens; and effects of threshold and nonthreshold models. Some discussion of the usefulness and limitations of epidemiological data is presented. Criteria for development of surrogate dose-response models are proposed for pathogens for which human data are lacking. Alternative dose-response models which consider biological plausibility are presented for predicting the probability of illness.

Document Type: Miscellaneous

Affiliations: 1: Office of Public Health and Science, Program Development, and Evaluation, Food Safety and Inspection Service, U.S. Department of Agriculture, 1400 Independence Ave., SW, Washington, D.C. 20250-3700, USA 2: Office of Policy, Program Development, and Evaluation, Food Safety and Inspection Service, U.S. Department of Agriculture, 1400 Independence Ave., SW, Washington, D.C. 20250-3700, USA

Publication date: November 1, 1998

More about this publication?
  • IAFP members must first sign in on the right to access full text articles of JFP

    First published in 1937, the Journal of Food Protection®, is a refereed monthly publication. Each issue contains scientific research and authoritative review articles reporting on a variety of topics in food science pertaining to food safety and quality. The Journal is internationally recognized as the leading publication in the field of food microbiology with a readership exceeding 11,000 scientists from 70 countries. The Journal of Food Protection® is indexed in Index Medicus, Current Contents, BIOSIS, PubMed, Medline, and many others.

    Print and online subscriptions are available to Members and Institutional subscribers. Online visitors who are not IAFP Members or journal subscribers will be charged on a pay-per-view basis. Information can be obtained by calling +1 800.369.6337; +1 515.276.3344; fax: +1 515.276.8655, E-mail: info@foodprotection.org or Web site: www.foodprotection.org
  • Information for Authors
  • Submit a Paper
  • Subscribe to this Title
  • Membership Information
  • Information for Advertisers
  • ingentaconnect is not responsible for the content or availability of external websites
Related content



Share Content

Access Key

Free Content
Free content
New Content
New content
Open Access Content
Open access content
Subscribed Content
Subscribed content
Free Trial Content
Free trial content
Cookie Policy
Cookie Policy
ingentaconnect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more