Quantitative microbiological risk assessment is a new and important scientific approach, allowing for the linking of data from food (throughout the whole lifecycle of food) with the data on human disease to provide a clear estimation of the impact of contaminated food on human public health. The first step to manage food safety risks includes the identification of foods, pathogens, or specific conditions that could potentially lead to foodborne illness, and assess the magnitude of impact on human health.

The four cornerstones of microbial food safety risk assessment are hazard identification, exposure assessment, hazard characterization, and risk characterization. These stages represent a systematic procedure for identifying adverse impacts and their associated probabilities arising from consumption of foods, possibly contaminated with microbial pathogens and/or microbial toxins.

The information provided for the risk assessment is necessary to take effective management decisions and assume corrective actions, when needed, in order to reduce foodborne disease.

Within the SMAS project, existing microbial risk assessment related information and data, with emphasis on meat products, is being collected and comprehensively and practically organized within this site. This data will be complemented by results from work on microbial modelling and risk assessment of raw meat (beef, pork, lamb) and ready to cook meat products. The main output will be predictive growth models, prevalence and concentration distributions referring to different pathogens (Listeria monocytogenes, Salmonella and Escherichia coli) and meat raw material (beef, pork, lamb).

The above information can be further used to assess microbiological risk of a variety of meat products such as fresh whole meat (beef, pork, lamb) cuts, ground meat (beef, pork, lamp) and ready to cook chilled meat (beef, pork) products stored under aerobic, or modified atmosphere packaging (MAP) conditions. Data on prevalence and concentration and meat chill chain conditions can be combined with validated predictive models and dose-response from state of art epidemiological data. A probabilistic approach allows assessment of risk of meat products at the time of consumption.

The ability to accurately estimate of risk of specific meat products at the time of consumption is an essential building block in the meat chill chain management system developed within the SMAS project.