Food safety objectives should integrate the variability of the concentration of pathogen.
The World Trade Organization introduced the concept of appropriate level of protection (ALOP) as a public health target. For this public health objective to be interpretable by the actors in the food chain, the concept of food safety objective (FSO) was proposed by the International Commission on Microbiological Specifications for Foods and adopted later by the Codex Alimentarius Food Hygiene Committee. The way to translate an ALOP into a FSO is still in debate. The purpose of this article is to develop a methodological tool to derive a FSO from an ALOP being expressed as a maximal annual marginal risk. We explore the different models relating the annual marginal risk to the parameters of the FSO depending on whether the variability in the survival probability and in the concentration of the pathogen are considered or not. If they are not, determination of the FSO is straightforward. If they are, we propose to use stochastic Monte Carlo simulation models and logistic discriminant analysis in order to determine which sets of parameters are compatible with the ALOP. The logistic discriminant function was chosen such that the kappa coefficient is maximized. We illustrate this method by the example of the risks of listeriosis and salmonellosis in one type of soft cheese. We conclude that the definition of the FSO should integrate three dimensions: the prevalence of contamination, the average concentration per contaminated typical serving, and the dispersion of the concentration among those servings.
Rieu
Emilie
E
Epidemiology and Risk Analysis Unit, National Veterinary School of Alfort, Maisons Alfort, Frame, France.
Duhem
Koenraad
K
Vindel
Elisabeth
E
Sanaa
Moez
M
D002611:Cheese; D003257:Consumer Product Safety; D004305:Dose-Response Relationship, Drug; D005506:Food Contamination; D005511:Food Handling; D005513:Food Inspection; D005516:Food Microbiology; D006801:Humans; D008088:Listeriosis / Q000517:prevention & control*; D016015:Logistic Models; D009010:Monte Carlo Method; D011336:Probability; D018570:Risk Assessment; D012449:Safety; D012480:Salmonella Infections / Q000517:prevention & control*