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Controlling disease outbreaks in wildlife using limited culling: modelling classical swine fever incursions in wild pigs in Australia
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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3311561/ https://www.ncbi.nlm.nih.gov/pubmed/22243996 http://dx.doi.org/10.1186/1297-9716-43-3 |
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author | Cowled, Brendan D Garner, M Graeme Negus, Katherine Ward, Michael P |
author_facet | Cowled, Brendan D Garner, M Graeme Negus, Katherine Ward, Michael P |
author_sort | Cowled, Brendan D |
collection | PubMed |
description | 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 km(2)) 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 km(2 )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. |
format | Online Article Text |
id | pubmed-3311561 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-33115612012-04-02 Controlling disease outbreaks in wildlife using limited culling: modelling classical swine fever incursions in wild pigs in Australia Cowled, Brendan D Garner, M Graeme Negus, Katherine Ward, Michael P Vet Res Research 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 km(2)) 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 km(2 )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. BioMed Central 2012 2012-01-16 /pmc/articles/PMC3311561/ /pubmed/22243996 http://dx.doi.org/10.1186/1297-9716-43-3 Text en Copyright ©2012 Cowled et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Cowled, Brendan D Garner, M Graeme Negus, Katherine Ward, Michael P Controlling disease outbreaks in wildlife using limited culling: modelling classical swine fever incursions in wild pigs in Australia |
title | Controlling disease outbreaks in wildlife using limited culling: modelling classical swine fever incursions in wild pigs in Australia |
title_full | Controlling disease outbreaks in wildlife using limited culling: modelling classical swine fever incursions in wild pigs in Australia |
title_fullStr | Controlling disease outbreaks in wildlife using limited culling: modelling classical swine fever incursions in wild pigs in Australia |
title_full_unstemmed | Controlling disease outbreaks in wildlife using limited culling: modelling classical swine fever incursions in wild pigs in Australia |
title_short | Controlling disease outbreaks in wildlife using limited culling: modelling classical swine fever incursions in wild pigs in Australia |
title_sort | controlling disease outbreaks in wildlife using limited culling: modelling classical swine fever incursions in wild pigs in australia |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3311561/ https://www.ncbi.nlm.nih.gov/pubmed/22243996 http://dx.doi.org/10.1186/1297-9716-43-3 |
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