Quantitative risk assessment of Listeria monocytogenes in bulk cooked meat from production to consumption in China: a Bayesian approach

Abstract BACKGROUND To estimate the public health risk related to cooked meat in bulk products contaminated with Listeria monocytogenes , a generic Bayesian network (BN) risk‐assessment model was developed to simulate influencing factors and processes of products from the industry level to the consumer level. To quantify the model, parameter values of prior distributions were acquired from the literature, websites, and expert opinions. Using the Markov chain Monte Carlo (MCMC) simulation approach, posterior probability distributions were calculated according to the incorporated evidence, which allowed us to predict various risks affected by processing variability from production to consumption. RESULTS The average risks of listeriosis from consuming cooked meat in bulk products are 8.40 × 10 −7 , 2.58 × 10 −8 , 8.24 × 10 −7 , and 1.05 × 10 −6 per meal for children, young people, elderly people, and pregnant women, respectively. The estimated mean number of listeriosis cases is 5 per 100 000 people per year in China. CONCLUSION Although only a conceptual BN model is given, it manifests the principles and characteristics of mathematical methods. The BN model can also provide significant benefits for quantitative risk assessment by incorporating all available data and by updating beliefs. © 2018 Society of Chemical Industry