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Classical full-scale QMRA is a valuable method to assess the effects of control measures on the public health risk of a pathogen–food product combination. However, development of these QMRA models is time consuming, data needs are substantial and it requires extensive modeling expertise. We therefore developed a simplified QMRA model especially aimed at comparing the risk of pathogen–food product combinations. The swift Quantitative Microbiological Risk Assessment (sQMRA) – tool is implemented in Microsoft Excel. Special attention is given to make the sQMRA tool insightful, for educational purposes. Like in full-scale QMRA, pathogen numbers are followed through the food chain, which in this case starts at retail and ends with the number of human cases of illness. The model is deterministic and includes cross-contamination and preparation (heating) in the kitchen and a dose–response relationship. The general setup of the sQMRA tool consists of consecutive questions for values of each of the 11 parameters, always followed by intermediate model output broken down into categories of contamination, cross-contamination and preparation. In a separate sheet, model input and output are summarized and exposure as well as cases are attributed to the distinguished categories. As a relative risk measure, intermediate and final model outputs are always compared with results from a full-scale QMRA of Campylobacter on chicken fillet. Example calculations with the sQMRA-tool were done for all combinations of Campylobacter spp. and Salmonella spp. with chicken fillet, filet americain (raw minced beef with mayonnaise) and table eggs. Data availability appeared to be partly poor. The predicted risk was highest for Salmonella spp. in table eggs and Campylobacter spp. in chicken fillet. Results indicate that the sQMRA-tool is useful for quickly obtaining relative risk estimates of pathogen–food combinations. It can thus serve as a guide for selection of combinations for applying full-scale QMRA, or for risk management – by facilitating the translation of the results of trend analysis or of a specific research project into terms of risk. |
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