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Table IV-2. General Criteria for Evaluating and Selecting Recommended Approaches to Establish Thresholds

Criteria Data Availability

Description Identification and review of currently available data that can

Data Quality

be used in any of the four approaches to establish a specific threshold. Evaluation of the available data for utility, completeness, and scientific soundness. Evaluation of the degree of uncertainty associated with the data.

1. Feasibility. The published and unpublished literature summarized in Sections II and III of this report were reviewed to determine the availability of the specific types of data needed for each of the approaches to establish thresholds. When necessary information was not available, the following questions were used to evaluate the existing information:

    • Is there surrogate or alternate information available that could be used?

    • Is the existing knowledge sufficient to support reasonable assumptions when specific data are not available?

    • What is the level of uncertainty associated with these data and assumptions?

  • 2.

    Uncertainty. Uncertainty is typically thought to arise from the lack of data or

information. Other sources of uncertainty are often considered to be relevant to scientific evaluations such as subjective judgment, statistical variation, sampling errors, and inherent randomness (Byrd and Cothern, 2000). Techniques are available to account for or measure some of these uncertainties. For example, the uncertainty in a dose-response model can be characterized using advanced techniques, such as model weighting, that measure the degree of credibility associated with the model results (Carrington, 1997). State-of-the-art food safety risk assessment models, such as the HHS/USDA Listeria monocytogenes risk assessment for ready-to-eat foods (HHS/USDA, 2003) also used techniques that separate uncertainty from biological variability. It is important to note that uncertainty is different from variability. Uncertainty reflects incomplete knowledge about a system or population which can be reduced with additional study. Variability reflects the fact that all systems or populations have inherent, biological heterogeneity that is not reducible through further measurement or study (Voysey et al., 2002). Sufficient knowledge is needed to account for both variability and uncertainty in order to evaluate the four approaches for establishing thresholds.

As described above, uncertainty factors are used in safety assessment calculations. Fitzhugh and Lehman (1954) originally proposed a single safety factor of 100-fold applied to animal data. The justification for this factor included both scientific issues and social values. The scientific issues included the possibility that humans may be more sensitive to chemicals than the rodents used in laboratory tests and that there may be substantial variability among individuals in a population. In general, as uncertainty increases, the uncertainty factor employed in a safety assessment should increase proportionally. As a matter of practice, uncertainty is not characterized in a safety assessment, either formally or subjectively, as is done in a quantitative risk assessment.

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