Recommended Practice Regarding Selection of Sensitivity Analysis Methods Applied to Microbial Food Safety Process Risk Models

ABSTRACT

A guideline is presented for selection of sensitivity analysis methods applied to microbial food safety process risk (MFSPR) models. The guideline provides useful boundaries and principles for selecting sensitivity analysis methods for MSFPR models. Although the guideline is predicated on a specific branch of risk assessment models related to food-borne diseases, the principles and recommendations provided are typically generally applicable to other types of risk models. Applicable situations include: prioritizing potential critical control points; identifying key sources of variability and uncertainty; and refinement, verification, and validation of a model. Based on the objective of the analysis, characteristics of the model under study, amount of detail expected from sensitivity analysis, and characteristics of the sensitivity analysis method, recommendations for selection of sensitivity analysis methods are provided. A decision framework for method selection is introduced. The decision framework can substantially facilitate the process of selecting a sensitivity analysis method.

Keywords:

• sensitivity analysis
• microbial food safety process risk model
• variability
• uncertainty.

ACKNOWLEDGMENTS

The work reported here was supported in part by Cooperative Agreement No. 58-0111-0-005 between the U.S. Department of Agriculture, Office of the Chief Economist, Office of the Risk Assessment and Cost Benefit Analysis (USDA/OCE/ ORACBA), and the Department of Civil, Construction, and Environmental Engineering at North Carolina State University. Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the authors and do not necessarily reflect the views of the U.S. Department of Agriculture. The authors thank J. Zheng for helpful reviews and comments on earlier versions of the work.

Notes

^a Depends on proper definition of factor levels

^b Assumes availability of simulation results from a Monte Carlo or similar analysis

^c Can be based upon expert judgment