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Escherichia Coli O157:H7 In Ground Beef: Review of a Draft Risk Assessment
many of its criticisms and suggestions regarding this model would apply to most previous and current microbial risk-assessment models if they were subject to the same intensity of review.
DESCRIPTION OF THE OVERALL MODELING APPROACH
The approach taken in this modeling effort is to create a highly complex probabilistic simulation model that extends from estimation of the pattern of prevalence of enterohemorrhagic E. coli (EHEC) among various types of cattle through propagation of the exposure predictions related to slaughter, processing, and preparation of meals to the estimation of the distribution of dose-response relationships. The dose-response relationships are derived by fitting predicted distributions of exposure to estimates of the population health risk attributable to ground beef as estimated from epidemiologic data.
In its final step, however, the model departs from the standard approach to risk assessment in a way that merits careful attention. Specifically, the risk characterization is carried out in part within the hazard-characterization stage by estimating (on the basis of epidemiologic data and investigations) the annual number of cases of EHEC illness associated with ground beef. Because the dose-response relationship is inferred from an algorithm that was designed to recreate samples from the distribution of the annual number of cases of EHEC illness, the risk estimates provided by the draft model cannot be considered to be independent of the epidemiological data.
Risk Modeling, But Not Risk Assessment as Commonly Understood
A key observation regarding the draft model is that it does not provide a risk assessment in the form that many readers would expect. To label the product a risk assessment implies that the effort is directed toward providing an estimate of risk by collecting evidence and applying mathematical tools; the estimate of risk would be a dependent output of the model. In particular, the use of the terms farm-to-fork and process risk model will imply to most readers that the many factors involved in the model are aggregated mathematically and propagated forward to generate an estimate of population health risk.
The standard approach to risk assessment is that the information input and the predictive output of the exposure assessment and the dose-response assessment are derived from independent scientific sources and that the dependent output is estimates of risk that are derived from the combination of the two subassessments. With an estimate of risk as the