Purpose: To use available data to gain insight into E. coli O157:H7 decay patterns and to propose quantitative approaches and decay models to describe the fate of the species in field-grown leafy vegetables.
Methods: Experimental data collected from diverse sources were tabulated and both individual and pooled data sets were subjected to statistical analyses to derive mathematical models describing decay patterns using MATLAB® software. The performance of the models was challenged against independent data sets and differences between modeling approaches were analyzed by developing a probabilistic exposure assessment model to estimate surviving E. coli O157:H7 populations on leafy vegetables at harvest. The probabilistic model was simulated by applying Monte-Carlo analysis implemented in @Risk®add-in for Excel.
Results: Regression analysis of individual data sets and pooled data indicated that E. coli O157:H7 followed a biphasic decay pattern that was satisfactorily described by the Weibull and Cerf models. Overall biphasic and monophasic models were generated that incorporated variability and uncertainty derived from the different data sets. A probabilistic exposure assessment model integrating the overall predictive models indicated that using a log-linear model (monophasic model) could lead to different risk estimates than those obtained with biphasic models. The log-linear approach yielded left-skewed distributions for surviving E. coli O157:H7 populations in addition to lower prevalence, and model did not account for an evident “tailing” effect in survivor curves.
Significance: This work represents the first critical assessment of the Weibull and Cerf models to describe the decay of E. coli O157:H7 in field-grown leafy vegetables and their suitability for microbial quantitative risk assessment.