Simulation of foot-and-mouth disease spread within an integrated livestock system in Texas, USA.

We used a simulation study to assess the impact of an incursion of foot-and-mouth disease (FMD) virus on the livestock industries in an 8-county area of the Panhandle region of Texas, USA. The study was conducted in a high-density livestock area, with an estimated number of cattle on-feed of approximately 1.8 million. We modified an existing stochastic, spatial simulation model to simulate 64 scenarios for planning and decision-making. Our scenarios simulated four different herd types for the index herd (company feedlot, backgrounder feedlot, large beef, backyard) and variations in three mitigation strategies (time-of-detection, vaccine availability, and surveillance during disease control). Under our assumptions about availability of resources to manage an outbreak, median epidemic lengths in the scenarios with commercial feedlot, backgrounder feedlot, large beef and backyard index herd types ranged from 28 to 52, 19 to 39, 18 to 32, and 18 to 36 days, respectively, and the average number of herds depopulated ranged from 4 to 101, 2 to 29, 1 to 15 and 1 to 18, respectively. Early detection of FMD in the index herd had the largest impact on reducing ( approximately 13-21 days) the length of epidemics and the number of herds ( approximately 5-34) depopulated. Although most predicted epidemics lasted only approximately 1-2 months, and <100 herds needed to be depopulated, large outbreaks lasting approximately 8-9 months with up to 230 herds depopulated might occur.

Effective surveillance strategies following a potential classical Swine Fever incursion in a remote wild pig population in North-Western Australia.

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.