Quantitative microbial risk analysis modelling is increasingly being used in food safety as a tool to evaluate health risks. Accurately forming such models can be very difficult due to the uncertainty in the available data. Second order Monte Carlo simulation allows for the inclusion of this uncertainty and separates it from the variability incorporated in the model. This modelling process is illustrated by performing a simple risk assessment on the infection of Campylobacter during chicken preparation at a typical New Zealand barbecue.
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