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Disease prioritization is motivated by the need to ensure that limited resources are targeted at the most important problems to achieve the greatest benefit in improving and maintaining human and animal health. Studies have prioritized a range of disease types, for example, zoonotic and foodborne diseases, using a range of criteria that describe potential disease impacts. This review describes the progression of disease prioritization methodology from ad hoc techniques to decision science methods (including multi-criteria decision analysis, conjoint analysis and probabilistic inversion), and describes how these methods aid defensible resource allocation. We discuss decision science in the context of disease prioritization to then review the development of disease prioritization studies. Structuring the prioritization and assessing decision-makers' preferences through value trade-offs between criteria within the decision context are identified as key factors that ensure transparency and reproducibility. Future directions for disease prioritization include the development of validation techniques, guidelines for model selection and neuroeconomics to gain a deeper understanding of decision-making.

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Diseases that are exotic to the pig industry in Australia were prioritised using a multi-criteria decision analysis framework that incorporated weights of importance for a range of criteria important to industry stakeholders. Measurements were collected for each disease for nine criteria that described potential disease impacts. A total score was calculated for each disease using a weighted sum value function that aggregated the nine disease criterion measurements and weights of importance for the criteria that were previously elicited from two groups of industry stakeholders. One stakeholder group placed most value on the impacts of disease on livestock, and one group placed more value on the zoonotic impacts of diseases. Prioritisation lists ordered by disease score were produced for both of these groups. Vesicular diseases were found to have the highest priority for the group valuing disease impacts on livestock, followed by acute forms of African and classical swine fever, then highly pathogenic porcine reproductive and respiratory syndrome. The group who valued zoonotic disease impacts prioritised rabies, followed by Japanese encephalitis, Eastern equine encephalitis and Nipah virus, interspersed with vesicular diseases. The multi-criteria framework used in this study systematically prioritised diseases using a multi-attribute theory based technique that provided transparency and repeatability in the process. Flexibility of the framework was demonstrated by aggregating the criterion weights from more than one stakeholder group with the disease measurements for the criteria. This technique allowed industry stakeholders to be active in resource allocation for their industry without the need to be disease experts. We believe it is the first prioritisation of livestock diseases using values provided by industry stakeholders. The prioritisation lists will be used by industry stakeholders to identify diseases for further risk analysis and disease spread modelling to understand biosecurity risks to this industry.

Canine rabies was endemic pre-urbanisation, yet little is known about how it persists in small populations of dogs typically seen in rural and remote regions. By simulating rabies outbreaks in such populations (50–90 dogs) using a network-based model, our objective was to determine if rabies-induced behavioural changes influence disease persistence. Behavioural changes–increased bite frequency and increased number or duration of contacts (disease-induced roaming or paralysis, respectively)–were found to be essential for disease propagation. Spread occurred in approximately 50% of model simulations and in these, very low case rates (2.0–2.6 cases/month) over long durations (95% range 20–473 days) were observed. Consequently, disease detection is a challenge, risking human infection and spread to other communities via dog movements. Even with 70% pre-emptive vaccination, spread occurred in >30% of model simulations (in these, median case rate was 1.5/month with 95% range of 15–275 days duration). We conclude that the social disruption caused by rabies-induced behavioural change is the key to explaining how rabies persists in small populations of dogs. Results suggest that vaccination of substantially greater than the recommended 70% of dog populations is required to prevent rabies emergence in currently free rural areas.