A swift Quantitative Microbiological Risk Assessment (sQMRA) tool
Eric G. Evers1, Jurgen E. Chardon1
1National Institute for Public Health and the Environment, P.O. Box 1, 3720 BA Bilthoven, The Netherlands
A simplified Quantitative Microbiological Risk Assessment (QMRA) model was especially developed to compare 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. 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. The sQMRA-tool can serve as a guide for selection of pathogen-food 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.
The authors welcome any comments, suggestions and questions. Please send them to Dr. Evers at email@example.com.
- A swift Quantitative Microbiological Risk Assessment (sQMRA) tool. Food Control 2010, 21, 319-330.
An improved sQMRA, published in 2016, is available here:
The sQMRA tool was commissioned by the Dutch Food and Consumer Product Safety Authority and developed by the National Institute for Public Health and the Environment (RIVM).