The uncertainty attendant to burden-of-illness estimates should be taken into account in comparing the public health impact of different foodborne pathogens. In this paper, decision analysis concepts are applied to the comparisons of pathogen-specific burden-of-illness estimates. In situations wherein the magnitude of uncertainty varies, the rank order of pathogen-specific burden-of-illness estimates is sensitive to the decisional criteria applied. To illustrate the magnitude of attendant uncertainty in pathogen-specific foodborne-illness estimates, probabilistic risk assessment methods are used to characterize the uncertainty regarding the burden of illness due to Escherichia coli O157:H7. The magnitude of uncertainty about the burden of food-related illness due to E. coli O157:H7 is substantial, ranging from less than 50,000 to more than 120,000 cases/year. This example underscores the importance of considering the uncertainty attendant to burden-of-illness estimates in comparing the public health impacts of different pathogens. Although some would argue that the expected value of the number of illnesses provides the "best estimate" for decision-making, this merely reflects a decision-making rule of convention and not a scientific truism.