Background: Burden of disease estimates, which combine mortality and morbidity into a single measure, are used increasingly for priority setting in disease control, prevention and surveillance. However, because there is no clear exclusion criterion for highly prevalent minimal disease in burden of disease studies its application may be restricted. The aim of this study was to apply a newly developed relevance criterion based on preferences of a population panel, and to compare burden of disease estimates of five foodborne pathogens calculated with and without application of this criterion. Methods: Preferences for twenty health states associated with foodborne disease were obtained from a population panel (n = 107) with the Visual Analogue Scale and the Time Trade-off (TTO) technique. The TTO preferences were used to derive the relevance criterion: if at least 50% of a panel of judges is willing to trade-off time in order to be restored to full health the health state is regarded as relevant, i.e. TTO median is greater than 0. Subsequently, the burden of disease of each of the five foodborne pathogens was calculated both with and without the relevance criterion. Results: The panel ranked the health states consistently. Of the twenty health states, three did not meet the preference-based relevance criterion. Application of the relevance criterion reduced the burden of disease estimate of all five foodborne pathogens. The reduction was especially significant for norovirus and rotavirus, decreasing with 94% and 78% respectively. Conclusion: Individual preferences elicited with the TTO from a population panel can be used to empirically derive a relevance criterion for burden of disease estimates. Application of this preference-based relevance criterion results in considerable changes in ranking of foodborne pathogens.

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Haagsma, J.A., Havelaar, A.H., Janssen, B.M.F., & Bonsel, G.J.. (2008). Disability adjusted life years and minimal disease: Application of a preference-based relevance criterion to rank enteric pathogens. Population Health Metrics, 6. doi:10.1186/1478-7954-6-7