Cargando…
Integrating Survey and Molecular Approaches to Better Understand Wildlife Disease Ecology
Infectious wildlife diseases have enormous global impacts, leading to human pandemics, global biodiversity declines and socio-economic hardship. Understanding how infection persists and is transmitted in wildlife is critical for managing diseases, but our understanding is limited. Our study aim was...
Autores principales: | , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2012
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3465323/ https://www.ncbi.nlm.nih.gov/pubmed/23071552 http://dx.doi.org/10.1371/journal.pone.0046310 |
_version_ | 1782245555470073856 |
---|---|
author | Cowled, Brendan D. Ward, Michael P. Laffan, Shawn W. Galea, Francesca Garner, M. Graeme MacDonald, Anna J. Marsh, Ian Muellner, Petra Negus, Katherine Quasim, Sumaiya Woolnough, Andrew P. Sarre, Stephen D. |
author_facet | Cowled, Brendan D. Ward, Michael P. Laffan, Shawn W. Galea, Francesca Garner, M. Graeme MacDonald, Anna J. Marsh, Ian Muellner, Petra Negus, Katherine Quasim, Sumaiya Woolnough, Andrew P. Sarre, Stephen D. |
author_sort | Cowled, Brendan D. |
collection | PubMed |
description | Infectious wildlife diseases have enormous global impacts, leading to human pandemics, global biodiversity declines and socio-economic hardship. Understanding how infection persists and is transmitted in wildlife is critical for managing diseases, but our understanding is limited. Our study aim was to better understand how infectious disease persists in wildlife populations by integrating genetics, ecology and epidemiology approaches. Specifically, we aimed to determine whether environmental or host factors were stronger drivers of Salmonella persistence or transmission within a remote and isolated wild pig (Sus scrofa) population. We determined the Salmonella infection status of wild pigs. Salmonella isolates were genotyped and a range of data was collected on putative risk factors for Salmonella transmission. We a priori identified several plausible biological hypotheses for Salmonella prevalence (cross sectional study design) versus transmission (molecular case series study design) and fit the data to these models. There were 543 wild pig Salmonella observations, sampled at 93 unique locations. Salmonella prevalence was 41% (95% confidence interval [CI]: 37–45%). The median Salmonella DICE coefficient (or Salmonella genetic similarity) was 52% (interquartile range [IQR]: 42–62%). Using the traditional cross sectional prevalence study design, the only supported model was based on the hypothesis that abundance of available ecological resources determines Salmonella prevalence in wild pigs. In the molecular study design, spatial proximity and herd membership as well as some individual risk factors (sex, condition score and relative density) determined transmission between pigs. Traditional cross sectional surveys and molecular epidemiological approaches are complementary and together can enhance understanding of disease ecology: abundance of ecological resources critical for wildlife influences Salmonella prevalence, whereas Salmonella transmission is driven by local spatial, social, density and individual factors, rather than resources. This enhanced understanding has implications for the control of diseases in wildlife populations. Attempts to manage wildlife disease using simplistic density approaches do not acknowledge the complexity of disease ecology. |
format | Online Article Text |
id | pubmed-3465323 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-34653232012-10-15 Integrating Survey and Molecular Approaches to Better Understand Wildlife Disease Ecology Cowled, Brendan D. Ward, Michael P. Laffan, Shawn W. Galea, Francesca Garner, M. Graeme MacDonald, Anna J. Marsh, Ian Muellner, Petra Negus, Katherine Quasim, Sumaiya Woolnough, Andrew P. Sarre, Stephen D. PLoS One Research Article Infectious wildlife diseases have enormous global impacts, leading to human pandemics, global biodiversity declines and socio-economic hardship. Understanding how infection persists and is transmitted in wildlife is critical for managing diseases, but our understanding is limited. Our study aim was to better understand how infectious disease persists in wildlife populations by integrating genetics, ecology and epidemiology approaches. Specifically, we aimed to determine whether environmental or host factors were stronger drivers of Salmonella persistence or transmission within a remote and isolated wild pig (Sus scrofa) population. We determined the Salmonella infection status of wild pigs. Salmonella isolates were genotyped and a range of data was collected on putative risk factors for Salmonella transmission. We a priori identified several plausible biological hypotheses for Salmonella prevalence (cross sectional study design) versus transmission (molecular case series study design) and fit the data to these models. There were 543 wild pig Salmonella observations, sampled at 93 unique locations. Salmonella prevalence was 41% (95% confidence interval [CI]: 37–45%). The median Salmonella DICE coefficient (or Salmonella genetic similarity) was 52% (interquartile range [IQR]: 42–62%). Using the traditional cross sectional prevalence study design, the only supported model was based on the hypothesis that abundance of available ecological resources determines Salmonella prevalence in wild pigs. In the molecular study design, spatial proximity and herd membership as well as some individual risk factors (sex, condition score and relative density) determined transmission between pigs. Traditional cross sectional surveys and molecular epidemiological approaches are complementary and together can enhance understanding of disease ecology: abundance of ecological resources critical for wildlife influences Salmonella prevalence, whereas Salmonella transmission is driven by local spatial, social, density and individual factors, rather than resources. This enhanced understanding has implications for the control of diseases in wildlife populations. Attempts to manage wildlife disease using simplistic density approaches do not acknowledge the complexity of disease ecology. Public Library of Science 2012-10-05 /pmc/articles/PMC3465323/ /pubmed/23071552 http://dx.doi.org/10.1371/journal.pone.0046310 Text en © 2012 Cowled et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Cowled, Brendan D. Ward, Michael P. Laffan, Shawn W. Galea, Francesca Garner, M. Graeme MacDonald, Anna J. Marsh, Ian Muellner, Petra Negus, Katherine Quasim, Sumaiya Woolnough, Andrew P. Sarre, Stephen D. Integrating Survey and Molecular Approaches to Better Understand Wildlife Disease Ecology |
title | Integrating Survey and Molecular Approaches to Better Understand Wildlife Disease Ecology |
title_full | Integrating Survey and Molecular Approaches to Better Understand Wildlife Disease Ecology |
title_fullStr | Integrating Survey and Molecular Approaches to Better Understand Wildlife Disease Ecology |
title_full_unstemmed | Integrating Survey and Molecular Approaches to Better Understand Wildlife Disease Ecology |
title_short | Integrating Survey and Molecular Approaches to Better Understand Wildlife Disease Ecology |
title_sort | integrating survey and molecular approaches to better understand wildlife disease ecology |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3465323/ https://www.ncbi.nlm.nih.gov/pubmed/23071552 http://dx.doi.org/10.1371/journal.pone.0046310 |
work_keys_str_mv | AT cowledbrendand integratingsurveyandmolecularapproachestobetterunderstandwildlifediseaseecology AT wardmichaelp integratingsurveyandmolecularapproachestobetterunderstandwildlifediseaseecology AT laffanshawnw integratingsurveyandmolecularapproachestobetterunderstandwildlifediseaseecology AT galeafrancesca integratingsurveyandmolecularapproachestobetterunderstandwildlifediseaseecology AT garnermgraeme integratingsurveyandmolecularapproachestobetterunderstandwildlifediseaseecology AT macdonaldannaj integratingsurveyandmolecularapproachestobetterunderstandwildlifediseaseecology AT marshian integratingsurveyandmolecularapproachestobetterunderstandwildlifediseaseecology AT muellnerpetra integratingsurveyandmolecularapproachestobetterunderstandwildlifediseaseecology AT neguskatherine integratingsurveyandmolecularapproachestobetterunderstandwildlifediseaseecology AT quasimsumaiya integratingsurveyandmolecularapproachestobetterunderstandwildlifediseaseecology AT woolnoughandrewp integratingsurveyandmolecularapproachestobetterunderstandwildlifediseaseecology AT sarrestephend integratingsurveyandmolecularapproachestobetterunderstandwildlifediseaseecology |