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Controlling disease outbreaks in wildlife using limited culling: modelling classical swine fever incursions in wild pigs in Australia.

ABSTRACT: Disease modelling is one approach for providing new insights into wildlife disease epidemiology. This paper describes a spatio-temporal, stochastic, susceptible- exposed-infected-recovered process model that simulates the potential spread of classical swine fever through a documented, large and free living wild pig population following a simulated incursion. The study area (300 000 km2) was in northern Australia. Published data on wild pig ecology from Australia, and international Classical Swine Fever data was used to parameterise the model. Sensitivity analyses revealed that herd density (best estimate 1-3 pigs km-2), daily herd movement distances (best estimate approximately 1 km), probability of infection transmission between herds (best estimate 0.75) and disease related herd mortality (best estimate 42%) were highly influential on epidemic size but that extraordinary movements of pigs and the yearly home range size of a pig herd were not. CSF generally established (98% of simulations) following a single point introduction. CSF spread at approximately 9 km2 per day with low incidence rates (< 2 herds per day) in an epidemic wave along contiguous habitat for several years, before dying out (when the epidemic arrived at the end of a contiguous sub-population or at a low density wild pig area). The low incidence rate indicates that surveillance for wildlife disease epidemics caused by short lived infections will be most efficient when surveillance is based on detection and investigation of clinical events, although this may not always be practical. Epidemics could be contained and eradicated with culling (aerial shooting) or vaccination when these were adequately implemented. It was apparent that the spatial structure, ecology and behaviour of wild populations must be accounted for during disease management in wildlife. An important finding was that it may only be necessary to cull or vaccinate relatively small proportions of a population to successfully contain and eradicate some wildlife disease epidemics.

SUBMITTER: Cowled BD

PROVIDER: S-EPMC3311561 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Controlling disease outbreaks in wildlife using limited culling: modelling classical swine fever incursions in wild pigs in Australia.

Cowled Brendan D BD Garner M Graeme MG Negus Katherine K Ward Michael P MP

Veterinary research 20120116

Disease modelling is one approach for providing new insights into wildlife disease epidemiology. This paper describes a spatio-temporal, stochastic, susceptible- exposed-infected-recovered process model that simulates the potential spread of classical swine fever through a documented, large and free living wild pig population following a simulated incursion. The study area (300 000 km2) was in northern Australia. Published data on wild pig ecology from Australia, and international Classical Swin ...[more]

PMID: 22243996

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Project description:Classical swine fever (CSF) is an infectious disease caused by Classical swine fever virus (CSFV), which is characterized by depression, high fever, extensive skin bleeding, leukopenia, anorexia, alternating constipation, and diarrhea. Hemorrhagic infarction of the spleen is the main characteristic pathological change following CSFV infection. Large-scale outbreaks of CSF are rare in China and are mainly distributed regionally. The clinical symptoms of CSF are not obvious, and show variation from typical to atypical symptoms, which makes diagnosis based on clinical symptoms and pathology challenging. In recent years, the incidence of CSF-immunized pig farms in China has increased and new CSFV gene subtypes have appeared, posing new challenges to the prevention and control of CSF in China. Changes in metabolites caused by viral infection reflect the pathogenic process. Metabonomics can reveal the trace metabolites of organisms; however, plasma metabonomics of CSFV-infected pigs have rarely been investigated. Therefore, we used an established pig CSFV infection model to study changes in plasma metabolites. The results showed significant differences in forty-five plasma metabolites at different time periods after CSFV infection in pigs, with an increase in twenty-five metabolites and a decrease in twenty metabolites. These changed metabolites were mainly attributed to the tricarboxylic acid cycle, amino acid cycle, sugar metabolism, and fat metabolism. Thirteen metabolic pathways changed significantly in CSFV-infected pigs, including tricarboxylic acid cycle, inositol phosphate metabolism, glycine, serine and threonine metabolism,lysine degradation, alanine, aspartate and glutamic acid metabolism, pantothenate and CoA biosynthesis, β-alanine metabolism, lysine degradation, arginine and proline metabolism, glycerolipid metabolism, phenylalanine metabolism, arachidonic acid metabolism, linoleic acid metabolism. Among these, changes in fatty acid biosynthesis and metabolism occurred at all time periods post-infection. These results indicate that CSFV infection in pigs could seriously alter metabolic pathways.

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Controlling disease outbreaks in wildlife using limited culling: modelling classical swine fever incursions in wild pigs in Australia.

Publications

Controlling disease outbreaks in wildlife using limited culling: modelling classical swine fever incursions in wild pigs in Australia.

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