Quantitative microbiological risk assessment (QMRA) of pathogens in food safety is well established, but steps are being taken to expand this methodology to food spoilage. Parallels can be drawn between the steps involved in a QMRA for pathogens and its application to specific spoilage organisms (SSO). During hazard characterisation for pathogens, the appropriate dose–response model is used to link the hazard level to the health outcome by estimating the probability of illness, resulting from the ingestion of a certain dose of the hazard. The dose–response model, in the case of food spoilage, may be translated into a spoilage‐response relationship linking the spoilage‐level with the probability the consumer will discard the food and not consume it. Such models are developed with sensory testing, assessing consumers sensitivity to microbial spoilage quality defects and correlating them to the SSO concentration. Ignoring food spoilage before the stated expiration date can lead to the final health risk being overestimated, since cases in which the food item poses a real risk to the consumer but is not consumed due to perceived spoilage are not excluded. Plenty of risk assessments have been carried out for pathogens in different RTE foods. What is missing is the integration of the two approaches into a single model that can estimate the risk of illness, factoring in the variability of consumer responses to spoilage. The spoilage‐response relationship was combined with a stochastic modelling approach for lactic acid bacteria (LAB) and Listeria monocytogenes growth, also taking into account microbial interaction between LAB and L. monocytogenes (Jameson effect) to increase accuracy. The comparison of results between the ‘Baseline’ and the ‘Spoilage‐informed’ approach showed significant difference in listeriosis cases, both for consumers under and over 65 years old. These results may suggest, that the hypothesis about overestimation of listeriosis risk in case of not taking into account product spoilage is correct. The combined QMRA model developed in the present study can be a useful tool for risk management decisions in the meat industry.
