Quantitative Risk Assessment of Listeria monocytogenes in Ready-to-Eat Fish Products

Introduction: Listeria monocytogenes is a common foodborne bacterium capable of causing severe disease, especially in persons with impaired immunity. Risk assessment is needed to evaluate the best risk management options to prevent listeriosis cases. Using Bayesian methods, as risk assessment tools has been proven useful due to their flexibility and ability to handle missing and fragmentary data.

Purpose: The purpose of this study was to assess the risk caused by L. monocytogenes in RTE fish products.

Methods: A Bayesian model, based on the Markov chain Monte Carlo computation, was developed for assessing the exposure for two populations: susceptible (elderly) and reference (working-age population). The exposure assessment model utilized data from national food survey (n=2,038) and L. monocytogenes surveys (n=1,083). This model was combined with an existing growth model and a dose-response model to predict the changes in risk (measured as annual illness cases in population) caused by the inappropriate storage practices of consumers.

Results: A mean dose in one contaminated portion varied largely with different scenarios. In scenarios where no growth was predicted, the mean dose per portion was approximately two log₁₀ cfu; whereas, scenarios with high refrigerator temperature and long storage period could elevate the mean dose to approximately seven log₁₀ cfu. Accordingly, predicted mean annual illness cases ranged from no cases to approximately 5,000 cases (median 1,600 cases) in the elderly population of size 600,000 and 130 cases (median 50 cases) in the reference population of size 2.8 million.

Significance: Temperature abuse and a long storage period was found to have a major effect on the predictions of mean annual listeriosis cases in the elderly.