Second-Order Modeling of Variability and Uncertainty in Microbial Hazard Characterization

• Published in: Journal of food protection Vol. 70; no. 2; pp. 363 - 372
• Main Authors: Vicari, A.S, Mokhtari, A, Morales, R.A, Jaykus, L.A, Frey, H.C, Slenning, B.D, Cowen, P
• Format: Journal Article
• Language: English
• Published: Des Moines, IA International Association of Milk, Food and Environmental Sanitarians 01.02.2007
• Subjects: Adolescent; Adult; Animals; bacterial contamination; Biological and medical sciences; Campylobacter jejuni; Campylobacter jejuni - pathogenicity; Child; Child, Preschool; Colony Count, Microbial; Consumer Product Safety; data collection; dose response; Female; food contamination; Food Contamination - analysis; Food Contamination - statistics & numerical data; Food industries; Food Microbiology; food pathogens; FoodNet (CDC); Fundamental and applied biological sciences. Psychology; Humans; Infant; Logistic Models; Male; microbial growth; microbiological risk assessment; Middle Aged; Models, Biological; Monte Carlo Method; predictive microbiology; Predictive Value of Tests; quantitative analysis; quantitative risk assessment; Risk Assessment; Characterization; Uncertainty; Modeling; Variability
• ISSN: 0362-028X; 1944-9097
• DOI: 10.4315/0362-028x-70.2.363

This study describes an analytical framework that permits quantitative consideration of variability and uncertainty in microbial hazard characterization. Second-order modeling that used two-dimensional Monte Carlo simulation and stratification into homogeneous population subgroups was applied to integrate uncertainty and variability. Specifically, the bootstrap method was used to simulate sampling error due to the limited sample size in microbial dose-response modeling. A data set from human feeding trials with Campylobacter jejuni was fitted to the log-logistic dose-response model, and results from the analysis of FoodNet surveillance data provided further information on variability and uncertainty in Campylobacter susceptibility due to the effect of age. Results of our analyses indicate that uncertainty associated with dose-response modeling has a dominating influence on the analytical outcome. In contrast, inclusion of the age factor has a limited impact. While the advocacy of more closely modeling variability in hazard characterization is warranted, the characterization of key sources of uncertainties and their consistent propagation throughout a microbial risk assessment actually appear of greater importance.