A genetic epidemiological model to describe resistance to an endemic bacterial disease in livestock: application to footrot in sheep
<p>Abstract</p> <p>Selection for resistance to an infectious disease not only improves resistance of animals, but also has the potential to reduce the pathogen challenge to contemporaries, especially when the population under selection is the main reservoir of pathogens. A model wa...
Main Authors: | , , |
---|---|
Format: | Article |
Language: | deu |
Published: |
BMC
2009-01-01
|
Series: | Genetics Selection Evolution |
Online Access: | http://www.gsejournal.org/content/41/1/19 |
id |
doaj-72625993f19b442b8a7218a0eddb1b10 |
---|---|
record_format |
Article |
spelling |
doaj-72625993f19b442b8a7218a0eddb1b102020-11-24T20:48:13ZdeuBMCGenetics Selection Evolution0999-193X1297-96862009-01-014111910.1186/1297-9686-41-19A genetic epidemiological model to describe resistance to an endemic bacterial disease in livestock: application to footrot in sheepConington JoanneNieuwhof GertBishop Stephen C<p>Abstract</p> <p>Selection for resistance to an infectious disease not only improves resistance of animals, but also has the potential to reduce the pathogen challenge to contemporaries, especially when the population under selection is the main reservoir of pathogens. A model was developed to describe the epidemiological cycle that animals in affected populations typically go through; viz. susceptible, latently infected, diseased and infectious, recovered and reverting back to susceptible through loss of immunity, and the rates at which animals move from one state to the next, along with effects on the pathogen population. The equilibrium prevalence was estimated as a function of these rates. The likely response to selection for increased resistance was predicted using a quantitative genetic threshold model and also by using epidemiological models with and without reduced pathogen burden. Models were standardised to achieve the same genetic response to one round of selection. The model was then applied to footrot in sheep. The only epidemiological parameters with major impacts for prediction of genetic progress were the rate at which animals recover from infection and the notional reproductive rate of the pathogen. There are few published estimates for these parameters, but plausible values for the rate of recovery would result in a response to selection, in terms of changes in the observed prevalence, double that predicted by purely genetic models in the medium term (<it>e.g</it>. 2–5 generations).</p> http://www.gsejournal.org/content/41/1/19 |
collection |
DOAJ |
language |
deu |
format |
Article |
sources |
DOAJ |
author |
Conington Joanne Nieuwhof Gert Bishop Stephen C |
spellingShingle |
Conington Joanne Nieuwhof Gert Bishop Stephen C A genetic epidemiological model to describe resistance to an endemic bacterial disease in livestock: application to footrot in sheep Genetics Selection Evolution |
author_facet |
Conington Joanne Nieuwhof Gert Bishop Stephen C |
author_sort |
Conington Joanne |
title |
A genetic epidemiological model to describe resistance to an endemic bacterial disease in livestock: application to footrot in sheep |
title_short |
A genetic epidemiological model to describe resistance to an endemic bacterial disease in livestock: application to footrot in sheep |
title_full |
A genetic epidemiological model to describe resistance to an endemic bacterial disease in livestock: application to footrot in sheep |
title_fullStr |
A genetic epidemiological model to describe resistance to an endemic bacterial disease in livestock: application to footrot in sheep |
title_full_unstemmed |
A genetic epidemiological model to describe resistance to an endemic bacterial disease in livestock: application to footrot in sheep |
title_sort |
genetic epidemiological model to describe resistance to an endemic bacterial disease in livestock: application to footrot in sheep |
publisher |
BMC |
series |
Genetics Selection Evolution |
issn |
0999-193X 1297-9686 |
publishDate |
2009-01-01 |
description |
<p>Abstract</p> <p>Selection for resistance to an infectious disease not only improves resistance of animals, but also has the potential to reduce the pathogen challenge to contemporaries, especially when the population under selection is the main reservoir of pathogens. A model was developed to describe the epidemiological cycle that animals in affected populations typically go through; viz. susceptible, latently infected, diseased and infectious, recovered and reverting back to susceptible through loss of immunity, and the rates at which animals move from one state to the next, along with effects on the pathogen population. The equilibrium prevalence was estimated as a function of these rates. The likely response to selection for increased resistance was predicted using a quantitative genetic threshold model and also by using epidemiological models with and without reduced pathogen burden. Models were standardised to achieve the same genetic response to one round of selection. The model was then applied to footrot in sheep. The only epidemiological parameters with major impacts for prediction of genetic progress were the rate at which animals recover from infection and the notional reproductive rate of the pathogen. There are few published estimates for these parameters, but plausible values for the rate of recovery would result in a response to selection, in terms of changes in the observed prevalence, double that predicted by purely genetic models in the medium term (<it>e.g</it>. 2–5 generations).</p> |
url |
http://www.gsejournal.org/content/41/1/19 |
work_keys_str_mv |
AT coningtonjoanne ageneticepidemiologicalmodeltodescriberesistancetoanendemicbacterialdiseaseinlivestockapplicationtofootrotinsheep AT nieuwhofgert ageneticepidemiologicalmodeltodescriberesistancetoanendemicbacterialdiseaseinlivestockapplicationtofootrotinsheep AT bishopstephenc ageneticepidemiologicalmodeltodescriberesistancetoanendemicbacterialdiseaseinlivestockapplicationtofootrotinsheep AT coningtonjoanne geneticepidemiologicalmodeltodescriberesistancetoanendemicbacterialdiseaseinlivestockapplicationtofootrotinsheep AT nieuwhofgert geneticepidemiologicalmodeltodescriberesistancetoanendemicbacterialdiseaseinlivestockapplicationtofootrotinsheep AT bishopstephenc geneticepidemiologicalmodeltodescriberesistancetoanendemicbacterialdiseaseinlivestockapplicationtofootrotinsheep |
_version_ |
1716808584715567104 |