Example 4: The establishment of a MC for lot-wise verification, based on a quantitative risk assessment Maarten Nauta and Jens Kirk Andersen on behalf of the drafting team

National Food Institute, Technical University of Denmark Specifics of this example The MC applies no “microbiological limit” (m, M), but a limit for the “Relative Risk” estimate associated with the food lot PO and FSO need not be defined Performance of a quantitative microbiological risk assessment model More practical when the pathogen is highly prevalent

National Food Institute, Technical University of Denmark Procedure Test n samples from a food lot –(semi-) quantitative data Perform a risk assessment on the test result Compare the risk of the food lot with an average (“baseline”) risk associated with the food –This baseline risk is obtained by the same risk assessment model Acceptability of food lot is conditioned on its Relative Risk RR –E.g. risk management decides a food lot with RR > 10 is non- conforming

National Food Institute, Technical University of Denmark PO and FSO need not be defined ALOP Human PO Food Chain FSO Meal/RTE MC

National Food Institute, Technical University of Denmark Requirements: A quantitative microbiological risk assessment (QMRA) –To obtain a human health risk estimate for a tested food lot based on n samples –Can be made user friendly A “baseline” data set –Represents the current occurrence and current population risk, or another representative situation –Provides a “baseline” risk estimate

National Food Institute, Technical University of Denmark Example on Campylobacter in poultry ALOP Human PO Food Chain FSO Meal/RTE MC RR = 0.271N *N >1000 MC defined by critical value of RR (e.g. RR>10) 20 meat /skin samples per food lot

National Food Institute, Technical University of Denmark Latest news Technical annex can be replaced by accepted paper. –Christensen et al 2012 Food Control A freely available user friendly tool for applying this method will be developed

National Food Institute, Technical University of Denmark Drafting team: Brazil –Andrea Regina de Oliveira Silva et al. Colombia –Blanca Cristina Olarte, Diana Ximena Correa et al. Costa Rica –Florencia Antillón Guerrero et al. Denmark –Jens Kirk Andersen, Annette Perge, Niels Nielsen, Maarten Nauta et al. Senegal –Amy Gassama Sow et al. ALA –Simone Machado