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Semi-stochastic models for Salmonella infection within finishing pig units in the UK()

A multi-group semi-stochastic model is formulated to describe Salmonella dynamics on a pig herd within the UK and assess whether farm structure has any effect on the dynamics. The models include both direct transmission and indirect (via free-living infectious units in the environment and airborne i...

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Autores principales: Berriman, Alexander D.C., Clancy, Damian, Clough, Helen E., Christley, Robert M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Elsevier 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3791402/
https://www.ncbi.nlm.nih.gov/pubmed/23796599
http://dx.doi.org/10.1016/j.mbs.2013.06.004
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author Berriman, Alexander D.C.
Clancy, Damian
Clough, Helen E.
Christley, Robert M.
author_facet Berriman, Alexander D.C.
Clancy, Damian
Clough, Helen E.
Christley, Robert M.
author_sort Berriman, Alexander D.C.
collection PubMed
description A multi-group semi-stochastic model is formulated to describe Salmonella dynamics on a pig herd within the UK and assess whether farm structure has any effect on the dynamics. The models include both direct transmission and indirect (via free-living infectious units in the environment and airborne infection). The basic reproduction number [Formula: see text] is also investigated. The models estimate approximately 24.6% and 25.4% of pigs at slaughter weight will be infected with Salmonella within a slatted-floored and solid-floored unit respectively, which corresponds to values found in previous abattoir and farm studies, suggesting that the model has reasonable validity. Analysis of the models identified the shedding rate to be of particular importance in the control of Salmonella spread, a finding also evident in an increase in the [Formula: see text] value.
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spelling pubmed-37914022013-10-07 Semi-stochastic models for Salmonella infection within finishing pig units in the UK() Berriman, Alexander D.C. Clancy, Damian Clough, Helen E. Christley, Robert M. Math Biosci Article A multi-group semi-stochastic model is formulated to describe Salmonella dynamics on a pig herd within the UK and assess whether farm structure has any effect on the dynamics. The models include both direct transmission and indirect (via free-living infectious units in the environment and airborne infection). The basic reproduction number [Formula: see text] is also investigated. The models estimate approximately 24.6% and 25.4% of pigs at slaughter weight will be infected with Salmonella within a slatted-floored and solid-floored unit respectively, which corresponds to values found in previous abattoir and farm studies, suggesting that the model has reasonable validity. Analysis of the models identified the shedding rate to be of particular importance in the control of Salmonella spread, a finding also evident in an increase in the [Formula: see text] value. American Elsevier 2013-10 /pmc/articles/PMC3791402/ /pubmed/23796599 http://dx.doi.org/10.1016/j.mbs.2013.06.004 Text en © 2013 The Authors https://creativecommons.org/licenses/by/3.0/ Open Access under CC BY 3.0 (https://creativecommons.org/licenses/by/3.0/) license
spellingShingle Article
Berriman, Alexander D.C.
Clancy, Damian
Clough, Helen E.
Christley, Robert M.
Semi-stochastic models for Salmonella infection within finishing pig units in the UK()
title Semi-stochastic models for Salmonella infection within finishing pig units in the UK()
title_full Semi-stochastic models for Salmonella infection within finishing pig units in the UK()
title_fullStr Semi-stochastic models for Salmonella infection within finishing pig units in the UK()
title_full_unstemmed Semi-stochastic models for Salmonella infection within finishing pig units in the UK()
title_short Semi-stochastic models for Salmonella infection within finishing pig units in the UK()
title_sort semi-stochastic models for salmonella infection within finishing pig units in the uk()
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3791402/
https://www.ncbi.nlm.nih.gov/pubmed/23796599
http://dx.doi.org/10.1016/j.mbs.2013.06.004
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