The sensitivity of an overall passive surveillance system is difficult to determine due to variability in factors such as disease characteristics, passive surveillance stakeholders and the likelihood that disease events will be reported and investigated. The WOAH Aquatic Animal Health Code also stipulates the primary evidence for historical freedom is passive surveillant information generated by a country’s early detection system that needs to be sufficiently sensitive.

Scenario tree modelling (STM) can be used to overcome those challenges. STM uses quantitative statistical methods to estimate the sensitivity of various components of the surveillance system (e.g. presentation of disease signs, disease recognition and reporting). These estimates can then be used to identify critical points in the system to which interventions can be targeted to improve the system. STM can be applied to any aquatic disease/industry of interest and there are some successful examples for terrestrial diseases/industries, both in Australia and overseas.

Two aquatic animal disease agents of trade and biosecurity significance, WSSV and megalocytiviruses, will be evaluated as case studies. These diseases are subject to import biosecurity measures and have significant production impacts, as they severely affect farmed and wild aquatic animal species that are valued by many stakeholders (e.g. aquaculture, capture fisheries, recreational fisheries and conservation groups). A sound STM assessment of each case study will support our early detection system through a quantitative evaluation of the speed of the detection, and improve our emergency disease response strategy by determining areas in our passive surveillance that, once strengthened, will provide a greater return on future investment.

As mentioned above, increasing the sensitivity of Australia’s passive surveillance is a national priority. This project is identified in AQUAPLAN 2022-2017 as Activity 3.3. The outcomes of this project are also used for other AQUAPLAN activities, National surveillance strategy (Activity 3.1) and Sector-specific surveillance plans (Activity 3.2). The data produced from this project will provide recommendations for various interventions to improve the overall performance of the passive surveillance system for the participating industries.

More broadly, the Fisheries Research and Development Corporation R&D Plan 2020-2025 identified building capability and capacity for biosecurity as a priority. In alignment with the R&D plan, successful outcomes of this project will improve understanding of disease transmission pathways which will enhance biosecurity practices. It will improve allocation of biosecurity resources (by identifying the most effective and cost-efficient way of investing resources in surveillance to get the best return), minimise biosecurity threats (by enhancing passive surveillance to accelerate an early detection) and improve market access for associated industry producers (by providing quantitative information on their passive surveillance sensitivity as a market access negotiation tool).