title: Suggestions for the construction, analysis and use of descriptive epidemiological models for the modernization of meat inspection.
abstract: There is consensus that scientifically validated, quantitative assessments of actual public health risks are a prerequisite for any sound modernization of current meat inspection procedures. This article outlines how such analyses could be conducted. Approaches that rely heavily upon extrapolations from theoretical dose-effect relationships are inadequate for the assessment of microbiological health risks associated with the production and consumption of meat. The use of highly structured and very elaborate descriptive epidemiological models covering the entire period from stable to table can be considered a promising solution. Health risks can be quantified by means of incidence rates and the influence of risk factors by means of odds ratios and (population) attributable fractions. A great advantage is that when it is not possible to quantify risks exactly, the descriptive models are detailed enough to be used in a hazard analysis critical control point (HACCP)-like approach and for writing validated codes of good manufacturing practice (GMP). There are, however, several conditions which have to be met before risk assessment can become the foundation of safety assurances for meat, such as active legislative support and the setting up of monitoring systems for zoonoses and other health hazards in animals and humans.
authors.affiliation: Department of the Science of Food of Animal Origin, Faculty of Veterinary Medicine, Utrecht University, The Netherlands. vvdo@pobox.ruu.nl
authors.forename: B R
authors.initials: BR
authors.lastname: Berends
authors.forename: F
authors.initials: F
authors.lastname: van Knapen
authors.forename: J M
authors.initials: JM
authors.lastname: Snijders
mesh_terms: D003625:Data Collection; D004784:Environmental Monitoring / Q000379:methods*; D005513:Food Inspection / Q000379:methods*; D008460:Meat / Q000592:standards*; D015203:Reproducibility of Results; D018570:Risk Assessment