Open Access
Vet. Res.
Volume 39, Number 6, November-December 2008
Number of page(s) 11
Published online 16 July 2008
How to cite this article Vet. Res. (2008) 39:53
How to cite this article: Vet. Res. (2008) 39:53
DOI: 10.1051/vetres:2008029

A mobility model for classical swine fever in feral pig populations

George Milne, Chloe Fermanis and Paul Johnston

School of Computer Science and Software Engineering, The University of Western Australia, Australia

Received 30 August 2007; accepted 10 July 2008; published online 16 July 2008

Abstract - We present a simulation model which explicitly captures the movement of wild animals over the landscape and the effect which herd mobility has on the temporal and spatial course of an epidemic. Using the example of classical swine fever in feral pig populations in the tropical savannas, we demonstrate that seasonal factors influencing population density and movement patterns are an important factor in the transmission of the disease. Pig population density is much greater at the start of the dry season than at the start of the wet season, with an epidemic most likely to occur if initiated at the start of the dry season. Spatial heterogeneity due to scarcity of water in the dry season causes herds to congregate around water sources. This concentration of herds, and the consequential isolation of sub-populations, reduces overall disease transmission compared with a model where the population is more evenly distributed over the landscape. The presence of adult male pig herds, which travel over greater distances than family herds, is shown to increase the overall scale of an outbreak in the dry season by connecting together otherwise isolated family herds. Eradication strategies are more likely to be successful in the dry season if they target long-range adult male herds. Our simulation method is generic and is equally applicable to other diseases where the host species is mobile.

Key words: classical swine fever / diseasemodelling / simulation / spatialmodel / feral and wild animal populations

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© INRA, EDP Sciences 2008