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Background: The definition of realistic models for microbial risk assessment (MRA) requires the inclusion of variability as it is part of the microbial response to stress. Most studies are based on the hypothesis that the variation in the microbial response observed under laboratory conditions is due only to two sources: variability (e.g. differences between cells) and uncertainty (e.g. experimental error); disregarding the impact of chance. In this study, we perform a critical review of this hypothesis, evidencing it may be unrealistic because chance can be more relevant than variability and uncertainty in some scenarios. Scope and approach: The impact of variability, uncertainty and chance for microbial survival is revised. Chance is identified as a possible relevant factor, different to variability and uncertainty because it is an inherent part of the system that is not associated with any biological mechanism. We derive probability distributions describing the impact of chance on microbial survival based on mechanistic hypotheses. These models are used to simulate inactivation experiments using a Monte Carlo algorithm. Key findings and conclusions: Our analytical and numerical results demonstrate the relevance of chance for microbial survival and, more generally, for MRA. When the probability of one cell surviving the treatment is low, chance becomes more relevant than variability or uncertainty. Chance can also introduce non-linearities in the survivor curves (fanning and tailing) that are usually associated with uncertainty and/or variability. Therefore, chance is a relevant factor that should be considered in MRA besides variability and uncertainty.
|Journal||Trends in Food Science and Technology|
|Issue number||Part B|
|Publication status||Published - Dec 2021|
- Food safety
- Quantitative microbiology
- Risk analysis
- Stochastic model
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