Effective Surveillance Strategies Following A Potential Classical Swine Fever Incursion in a Remote Wild Pig Population in North-Western Australia

Abstract

Early disease detection and efficient methods of proving disease freedom can substantially improve the response to incursions of important transboundary animal diseases in previously free regions. We used a spatially explicit, stochastic disease spread model to simulate the spread of classical swine fever in wild pigs in a remote region of northern Australia and to assess the performance of disease surveillance strategies to detect infection at different time points and to delineate the size of the resulting outbreak. Although disease would likely be detected, simple random sampling was suboptimal. Radial and leapfrog sampling improved the effectiveness of surveillance at various stages of the simulated disease incursion. This work indicates that at earlier stages, radial sampling can reduce epidemic length and achieve faster outbreak delineation and control, but at later stages leapfrog sampling will outperform radial sampling in relation to supporting faster disease control with a less-extensive outbreak area. Due to the complexity of wildlife population dynamics and group behaviour, a targeted approach to surveillance needs to be implemented for the efficient use of resources and time. Using a more situation-based surveillance approach and accounting for disease distribution and the time period over which an epidemic has occurred is the best way to approach the selection of an appropriate surveillance strategy.