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NUSAP: a method to evaluate the quality of assumptions in quantitative microbial risk assessment

Author

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  • Ides Boone
  • Yves Van der Stede
  • Jeroen Dewulf
  • Winy Messens
  • Marc Aerts
  • Georges Daube
  • Koen Mintiens

Abstract

The Numeral Unit Spread Assessment Pedigree (NUSAP) system was implemented to evaluate assumptions in a quantitative microbial risk assessment (QMRA) model for Salmonella spp. in minced pork meat. This QMRA model allows the testing of mitigation strategies for the reduction of human salmonellosis and aims to serve as a basis for science-based policy making. The NUSAP method was used to assess the subjective component of assumptions in the QMRA model by a set of four pedigree criteria: 'the influence of situational limitations', 'plausibility', 'choice space' and 'the agreement among peers'. After identifying 13 key assumptions relevant for the QMRA model, a workshop was organized to assess the importance of these assumptions on the output of the QMRA. The quality of the assumptions was visualized using diagnostic and kite diagrams. The diagnostic diagram pinpointed assumptions with a high degree of subjectivity and a high 'expected influence on the model results' score. Examples of those assumptions that should be dealt with care are the assumptions regarding the concentration of Salmonella on the pig carcass at the beginning of the slaughter process and the assumptions related to the Salmonella prevalence in the slaughter process. The kite diagrams allowed a clear overview of the pedigree scores for each assumption as well as a representation of expert (dis)agreement. The evaluation of the assumptions using the NUSAP system enhanced the debate on the uncertainty and its communication in the results of a QMRA model. It highlighted the model's strong and weak points and was helpful for redesigning critical modules. Since the evaluation of assumptions allows a more critical approach of the QMRA process, it is useful for policy makers as it aims to increase the transparency and acceptance of management decisions based on a QMRA model.

Suggested Citation

  • Ides Boone & Yves Van der Stede & Jeroen Dewulf & Winy Messens & Marc Aerts & Georges Daube & Koen Mintiens, 2010. "NUSAP: a method to evaluate the quality of assumptions in quantitative microbial risk assessment," Journal of Risk Research, Taylor & Francis Journals, vol. 13(3), pages 337-352, April.
    • Handle: RePEc:taf:jriskr:v:13:y:2010:i:3:p:337-352
    DOI: 10.1080/13669870903564574
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    References listed on IDEAS

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    1. Ides Boone & Yves Van der Stede & Kaatje Bollaerts & David Vose & Dominiek Maes & Jeroen Dewulf & Winy Messens & Georges Daube & Marc Aerts & Koen Mintiens, 2009. "NUSAP Method for Evaluating the Data Quality in a Quantitative Microbial Risk Assessment Model for Salmonella in the Pork Production Chain," Risk Analysis, John Wiley & Sons, vol. 29(4), pages 502-517, April.
    2. Jeroen P. Van Der Sluijs & Matthieu Craye & Silvio Funtowicz & Penny Kloprogge & Jerry Ravetz & James Risbey, 2005. "Combining Quantitative and Qualitative Measures of Uncertainty in Model‐Based Environmental Assessment: The NUSAP System," Risk Analysis, John Wiley & Sons, vol. 25(2), pages 481-492, April.
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    3. Berner, Christine Louise & Flage, Roger, 2017. "Creating risk management strategies based on uncertain assumptions and aspects from assumption-based planning," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 10-19.
    4. Xavier Romão & Esmeralda Paupério, 2016. "A framework to assess quality and uncertainty in disaster loss data," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 83(2), pages 1077-1102, September.
    5. Kaatje Bollaerts & Winy Messens & Marc Aerts & Jeroen Dewulf & Dominiek Maes & Koen Grijspeerdt & Yves Van der Stede, 2010. "Evaluation of Scenarios for Reducing Human Salmonellosis Through Household Consumption of Fresh Minced Pork Meat," Risk Analysis, John Wiley & Sons, vol. 30(5), pages 853-865, May.
    6. Tasneem Bani-Mustafa & Nicola Pedroni & Enrico Zio & Dominique Vasseur & Francois Beaudouin, 2020. "A hierarchical tree-based decision-making approach for assessing the relative trustworthiness of risk assessment models," Journal of Risk and Reliability, , vol. 234(6), pages 748-763, December.
    7. Martijn Bouwknegt & Anne B. Knol & Jeroen P. van der Sluijs & Eric G. Evers, 2014. "Uncertainty of Population Risk Estimates for Pathogens Based on QMRA or Epidemiology: A Case Study of Campylobacter in the Netherlands," Risk Analysis, John Wiley & Sons, vol. 34(5), pages 847-864, May.
    8. Berner, Christine Louise & Flage, Roger, 2016. "Comparing and integrating the NUSAP notational scheme with an uncertainty based risk perspective," Reliability Engineering and System Safety, Elsevier, vol. 156(C), pages 185-194.
    9. Bjørnsen, Kjartan & Aven, Terje, 2019. "Risk aggregation: What does it really mean?," Reliability Engineering and System Safety, Elsevier, vol. 191(C).

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