Comparison of sensitivity analysis methods based on applications to a food safety risk assessment model

Abstract

Sensitivity analysis (SA) methods are a valuable tool for identifying critical control points (CCPs), which is one of the important steps in the hazard analysis and CCP approach that is used to ensure safe food. There are many SA methods used across various disciplines. Furthermore, food safety process risk models pose challenges because they often are highly nonlinear, contain thresholds, and have discrete inputs. Therefore, it is useful to compare and evaluate SA methods based upon applications to an example food safety risk model. Ten SA methods were applied to a draft Vibrio parahaemolyticus (Vp) risk assessment model developed by the Food and Drug Administration. The model was modified so that all inputs were independent. Rankings of key inputs from different methods were compared. Inputs such as water temperature, number of oysters per meal, and the distributional assumption for the unrefrigerated time were the most important inputs, whereas time on water, fraction of pathogenic Vp, and the distributional assumption for the weight of oysters were the least important inputs. Most of the methods gave a similar ranking of key inputs even though the methods differed in terms of being graphical, mathematical, or statistical, accounting for individual effects or joint effect of inputs, and being model dependent or model independent. A key recommendation is that methods be further compared by application on different and more complex food safety models. Model independent methods, such as ANOVA, mutual information index, and scatter plots, are expected to be more robust than others evaluated.