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Demographic stochasticity drives epidemiological patterns in wildlife with implications for diseases and population management

Infectious diseases raise many concerns for wildlife and new insights must be gained to manage infected populations. Wild ungulates provide opportunities to gain such insights as they host many pathogens. Using modelling and data collected from an intensively monitored population of Pyrenean chamois...

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Autores principales: Lambert, Sébastien, Ezanno, Pauline, Garel, Mathieu, Gilot-Fromont, Emmanuelle
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6237989/
https://www.ncbi.nlm.nih.gov/pubmed/30442961
http://dx.doi.org/10.1038/s41598-018-34623-0
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author Lambert, Sébastien
Ezanno, Pauline
Garel, Mathieu
Gilot-Fromont, Emmanuelle
author_facet Lambert, Sébastien
Ezanno, Pauline
Garel, Mathieu
Gilot-Fromont, Emmanuelle
author_sort Lambert, Sébastien
collection PubMed
description Infectious diseases raise many concerns for wildlife and new insights must be gained to manage infected populations. Wild ungulates provide opportunities to gain such insights as they host many pathogens. Using modelling and data collected from an intensively monitored population of Pyrenean chamois, we investigated the role of stochastic processes in governing epidemiological patterns of pestivirus spread in both protected and hunted populations. We showed that demographic stochasticity led to three epidemiological outcomes: early infection fade-out, epidemic outbreaks with population collapse, either followed by virus extinction or by endemic situations. Without re-introduction, the virus faded out in >50% of replications within 4 years and did not persist >20 years. Test-and-cull of infected animals and vaccination had limited effects relative to the efforts devoted, especially in hunted populations in which only quota reduction somewhat improve population recovery. Success of these strategies also relied on the maintenance of a high level of surveillance of hunter-harvested animals. Our findings suggested that, while surveillance and maintenance of population levels at intermediate densities to avoid large epidemics are useful at any time, a ‘do nothing’ approach during epidemics could be the ‘least bad’ management strategy in populations of ungulates species facing pestivirus infection.
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spelling pubmed-62379892018-11-23 Demographic stochasticity drives epidemiological patterns in wildlife with implications for diseases and population management Lambert, Sébastien Ezanno, Pauline Garel, Mathieu Gilot-Fromont, Emmanuelle Sci Rep Article Infectious diseases raise many concerns for wildlife and new insights must be gained to manage infected populations. Wild ungulates provide opportunities to gain such insights as they host many pathogens. Using modelling and data collected from an intensively monitored population of Pyrenean chamois, we investigated the role of stochastic processes in governing epidemiological patterns of pestivirus spread in both protected and hunted populations. We showed that demographic stochasticity led to three epidemiological outcomes: early infection fade-out, epidemic outbreaks with population collapse, either followed by virus extinction or by endemic situations. Without re-introduction, the virus faded out in >50% of replications within 4 years and did not persist >20 years. Test-and-cull of infected animals and vaccination had limited effects relative to the efforts devoted, especially in hunted populations in which only quota reduction somewhat improve population recovery. Success of these strategies also relied on the maintenance of a high level of surveillance of hunter-harvested animals. Our findings suggested that, while surveillance and maintenance of population levels at intermediate densities to avoid large epidemics are useful at any time, a ‘do nothing’ approach during epidemics could be the ‘least bad’ management strategy in populations of ungulates species facing pestivirus infection. Nature Publishing Group UK 2018-11-15 /pmc/articles/PMC6237989/ /pubmed/30442961 http://dx.doi.org/10.1038/s41598-018-34623-0 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Lambert, Sébastien
Ezanno, Pauline
Garel, Mathieu
Gilot-Fromont, Emmanuelle
Demographic stochasticity drives epidemiological patterns in wildlife with implications for diseases and population management
title Demographic stochasticity drives epidemiological patterns in wildlife with implications for diseases and population management
title_full Demographic stochasticity drives epidemiological patterns in wildlife with implications for diseases and population management
title_fullStr Demographic stochasticity drives epidemiological patterns in wildlife with implications for diseases and population management
title_full_unstemmed Demographic stochasticity drives epidemiological patterns in wildlife with implications for diseases and population management
title_short Demographic stochasticity drives epidemiological patterns in wildlife with implications for diseases and population management
title_sort demographic stochasticity drives epidemiological patterns in wildlife with implications for diseases and population management
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6237989/
https://www.ncbi.nlm.nih.gov/pubmed/30442961
http://dx.doi.org/10.1038/s41598-018-34623-0
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