SUMMARY: 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 fromad hoctechniques 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.

Summary: Emerging and re-emerging infectious disease (EID) events can have devastating human, animal and environmental health impacts. The emergence of EIDs has been associated with interconnected economic, social and environmental changes. Understanding these changes is crucial for EID preparedness and subsequent prevention and control of EID events. The aim of this review is to describe tools currently available for identification, prioritization and investigation of EIDs impacting human and animal health, and how these might be integrated into a systematic approach for directing EID preparedness. Environmental scanning, foresight programmes, horizon scanning and surveillance are used to collect and assess information for rapidly responding to EIDs and to anticipate drivers of emergence for mitigating future EID impacts. Prioritization of EIDs − using transparent and repeatable methods − based on disease impacts and the importance of those impacts to decision-makers can then be used for more efficient resource allocation for prevention and control. Risk assessment and simulation modelling methods assess the likelihood of EIDs occurring, define impact and identify mitigation strategies. Each of these tools has a role to play individually; however, we propose integration of these tools into a framework that enhances the development of tactical and strategic plans for emerging risk preparedness.

Rabies is a globally distributed virus that causes approximately 60,00 human deaths annually with >99% of cases caused by dog bites. Australia is currently canine-rabies free. However, the recent eastward spread of rabies in the Indonesian archipelago has increased the probability of rabies entry into northern Australian communities. In addition, many northern Australian communities have large populations of free-roaming dogs, capable of maintaining rabies should an incursion occur. A risk assessment of rabies entry and transmission into these communities is needed to target control and surveillance measures. Illegal transportation of rabies-infected dogs via boat landings is a high-risk entry pathway and was the focus of the current study. A quantitative, stochastic, risk assessment model was developed to evaluate the risk of rabies entry into north-west Cape York Peninsula, Australia and rabies introduction to resident dogs in one of the communities via transport of rabies-infected dogs on illegal Indonesian fishing boats. Parameter distributions were derived from expert-opinion, literature and analysis of field studies. The estimated median probability of rabies entry into north-west Cape York Peninsula and into Seisia from individual fishing boats was 1.9x10-4/boat and 8.7x10-6/boat, respectively. The estimated annual probability that at least one rabies-infected dog enters north-west Cape York Peninsula and into Seisia was 5.5 x10-3 and 3.5x10-4, respectively. The estimated median probability of rabies introduction into Seisia was 4.7x10-8/boat and the estimated annual probability that at least one rabies-infected dog causes rabies transmission in a resident Seisia dog was 8.3x10-5. Sensitivity analysis using the Sobol method highlighted some parameters as influential, including but not limited to the prevalence of rabies in Indonesia, the probability of a dog on board an Indonesian fishing boat and the probability of a Seisia dog being on the beach. Overall, the probabilities of rabies entry into north-west Cape York Peninsula and rabies introduction into Seisia are low. However, the potential devastating consequences of a rabies incursion in this region make this a non-negligible risk.