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Point of truth calibration for disease prioritisation-A case study of prioritisation of exotic diseases for the pig industry in Australia.

The objective of this study was to trial point of truth calibration (POTCal) as a novel method for disease prioritisation. To illustrate the application of this method, we used a previously described case-study of prioritisation of exotic diseases for the pig industry in Australia. Disease scenarios were constructed from criteria which described potential impact and pig-producers were asked to score the importance of each scenario. POTCal was used to model participants' estimates of disease importance as a function of the criteria, to derive a predictive model to prioritise a range of exotic diseases. The best validation of producers' estimates was achieved using a model derived from all responses. The highest weighted criteria were attack rate, case fatality rate and market loss, and the highest priority diseases were the vesicular diseases followed by swine fevers and zoonotic encephalitides. Comparison of results with a previous study in which probabilistic inversion was used to prioritise diseases for the same group of producers highlighted differences between disease prioritisation methods. Overall, this study demonstrated that POTCal can be used for disease prioritisation. An advantage of POTCal is that valid models can be developed that reflect decision-makers' heuristics. Specifically, this evaluation of the use of POTCal in animal health illustrates how the judgements of participants can be incorporated into a decision-making process. Further research is needed to investigate the influence of scenarios presented to participants during POTCal evaluations, and the robustness of this approach applied to different disease issues (e.g. exotic versus endemic) and production types (e.g. intensive versus extensive). To our knowledge, this is the first report of the use of POTCal for disease prioritisation.

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