Scientists at the Finnish Food Safety Authority Evira have developed a mathematical model for overcoming data gaps when assessing food safety risks during meat processing.

Risk assessments related to food safety over more than one step of the production line can be hampered by a lack of detailed quantitative data, according to Evira.

A Bayesian hidden variable model was developed to overcome the problem of limited data and was put to work to evaluate the prevalence of microbes in the production of pork and any changes from one stage of the production chain to another.

Results of different tests of different types from these various points in the production chain were computed into the model. The output of the model is obtained in the form of a probability distribution, which describes the remaining uncertainty. The magnitude of the microbial risk is measured by calculating probabilities and the results can then be used to inform decision making.

The model can also be used to evaluate the effectiveness of steps to reduce or eradicate food safety risks or other background variables that may affect risks.

In the case of pork production, the test results and the model estimated that the prevalence of one or more of the three bacteria tracked in Finnish pork is 1-11%. In the slaughterhouse, if the head were removed and the rectum sealed off, this figure could be reduced to 0-2%.

Looking forward, Evira said that the output of the model can be utilised in determining the ideal monitoring point for microbes and in planning risk control action for the production chain.

The model was developed within the framework of a research project in which the Department of Food Hygiene and Environmental Health at the University of Helsinki participated. Funding was provided by the Ministry of Agriculture and Forestry, Finland.