Scenario tree modelling to assess the sensitivity of white spot syndrome virus surveillance in Australian prawn aquaculture.

White spot disease (WSD) is of major economic significance to the Australian prawn industry. Since 2016, Australia has experienced several devastating outbreaks in farmed prawns. White spot syndrome virus (WSSV) has also been detected in healthy wild prawns in southeast Queensland and northern New South Wales. Subsequently, Australian prawn producers have undertaken extensive review of their on-farm biosecurity practices to mitigate against future outbreaks. In this study, we developed a stochastic scenario tree model of WSSV surveillance in the Australian prawn aquaculture industry to 1) estimate the confidence of freedom from infection in this compartment, and 2) determine the sensitivity of early detection surveillance. We also sought to understand whether the use of active surveillance during grow-out would enhance surveillance sensitivity. Australia's current approach to WSSV surveillance in the prawn aquaculture industry was found to be both sensitive and efficient to demonstrate freedom from infection over a production cycle. Early detection sensitivity, or the probability of detecting a WSSV incursion in the first affected epidemiological unit prior to onwards transmission, was low, due to the rapid spread of WSSV. Passive surveillance was, on average, more sensitive for early disease detection compared to active surveillance, even under a hypothetical scenario of daily qPCR-based testing of all grow-out ponds. The most efficient way to increase WSSV early detection sensitivity is to increase passive surveillance sensitivity by promoting awareness of the importance of rapid detection, and encouraging reporting, investigation, sampling and testing of diseased units.