title: Characterizing uncertainty when evaluating risk management metrics: risk assessment modeling of Listeria monocytogenes contamination in ready-to-eat deli meats.
abstract: This report illustrates how the uncertainty about food safety metrics may influence the selection of a performance objective (PO). To accomplish this goal, we developed a model concerning Listeria monocytogenes in ready-to-eat (RTE) deli meats. This application used a second order Monte Carlo model that simulates L. monocytogenes concentrations through a series of steps: the food-processing establishment, transport, retail, the consumer's home and consumption. The model accounted for growth inhibitor use, retail cross contamination, and applied an FAO/WHO dose response model for evaluating the probability of illness. An appropriate level of protection (ALOP) risk metric was selected as the average risk of illness per serving across all consumed servings-per-annum and the model was used to solve for the corresponding performance objective (PO) risk metric as the maximum allowable L. monocytogenes concentration (cfu/g) at the processing establishment where regulatory monitoring would occur. Given uncertainty about model inputs, an uncertainty distribution of the PO was estimated. Additionally, we considered how RTE deli meats contaminated at levels above the PO would be handled by the industry using three alternative approaches. Points on the PO distribution represent the probability that - if the industry complies with a particular PO - the resulting risk-per-serving is less than or equal to the target ALOP. For example, assuming (1) a target ALOP of -6.41 log10 risk of illness per serving, (2) industry concentrations above the PO that are re-distributed throughout the remaining concentration distribution and (3) no dose response uncertainty, establishment PO's of -4.98 and -4.39 log10 cfu/g would be required for 90% and 75% confidence that the target ALOP is met, respectively. The PO concentrations from this example scenario are more stringent than the current typical monitoring level of an absence in 25 g (i.e., -1.40 log10 cfu/g) or a stricter criteria of absence in 125 g (i.e., -2.1 log10 cfu/g). This example, and others, demonstrates that a PO for L. monocytogenes would be far below any current monitoring capabilities. Furthermore, this work highlights the demands placed on risk managers and risk assessors when applying uncertain risk models to the current risk metric framework.
authors: Civil and Environmental Engineering Department, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA. dang@vt.edu
authors: Daniel
authors: D
authors: Gallagher
authors: Eric D
authors: ED
authors: Ebel
authors: Owen
authors: O
authors: Gallagher
authors: David
authors: D
authors: Labarre
authors: Michael S
authors: MS
authors: Williams
authors: Neal J
authors: NJ
authors: Golden
authors: Régis
authors: R
authors: Pouillot
authors: Kerry L
authors: KL
authors: Dearfield
authors: Janell
authors: J
authors: Kause
mesh_terms: D005506:Food Contamination / Q000517:prevention & control*; D005511:Food Handling / Q000592:standards; D005516:Food Microbiology / Q000458:organization & administration*; D006801:Humans; D008089:Listeria monocytogenes / Q000254:growth & development* / Q000302:isolation & purification; D008452:Maximum Allowable Concentration; D008460:Meat / Q000382:microbiology*; D008461:Meat Products / Q000382:microbiology; D015233:Models, Statistical; D009010:Monte Carlo Method; D018570:Risk Assessment; D012308:Risk Management; D035501:Uncertainty