Second-order modeling of variability and uncertainty in microbial hazard characterization.
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.
Vicari
Andrea S
AS
Department of Population Health and Pathobiology, North Carolina State University, Raleigh, North Carolina 27605-8401, USA.
Mokhtari
Amirhossein
A
Morales
Roberta A
RA
Jaykus
Lee-Ann
LA
Frey
H Christopher
HC
Slenning
Barrett D
BD
Cowen
Peter
P
D000293:Adolescent; D000328:Adult; D000818:Animals; D016123:Campylobacter jejuni / Q000472:pathogenicity*; D002648:Child; D002675:Child, Preschool; D015169:Colony Count, Microbial; D003257:Consumer Product Safety; D005260:Female; D005506:Food Contamination / Q000032:analysis* / Q000706:statistics & numerical data; D005516:Food Microbiology; D006801:Humans; D007223:Infant; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D009010:Monte Carlo Method; D011237:Predictive Value of Tests; D018570:Risk Assessment