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Individual-based modelling and control of bovine brucellosis

We present a theoretical approach to control bovine brucellosis. We have used individual-based modelling, which is a network-type alternative to compartmental models. Our model thus considers heterogeneous populations, and spatial aspects such as migration among herds and control actions described a...

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Detalles Bibliográficos
Autores principales: Nepomuceno, Erivelton G., Barbosa, Alípio M., Silva, Marcos X., Perc, Matjaž
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society Publishing 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5990817/
https://www.ncbi.nlm.nih.gov/pubmed/29892455
http://dx.doi.org/10.1098/rsos.180200
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author Nepomuceno, Erivelton G.
Barbosa, Alípio M.
Silva, Marcos X.
Perc, Matjaž
author_facet Nepomuceno, Erivelton G.
Barbosa, Alípio M.
Silva, Marcos X.
Perc, Matjaž
author_sort Nepomuceno, Erivelton G.
collection PubMed
description We present a theoretical approach to control bovine brucellosis. We have used individual-based modelling, which is a network-type alternative to compartmental models. Our model thus considers heterogeneous populations, and spatial aspects such as migration among herds and control actions described as pulse interventions are also easily implemented. We show that individual-based modelling reproduces the mean field behaviour of an equivalent compartmental model. Details of this process, as well as flowcharts, are provided to facilitate the reproduction of the presented results. We further investigate three numerical examples using real parameters of herds in the São Paulo state of Brazil, in scenarios which explore eradication, continuous and pulsed vaccination and meta-population effects. The obtained results are in good agreement with the expected behaviour of this disease, which ultimately showcases the effectiveness of our theory.
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spelling pubmed-59908172018-06-11 Individual-based modelling and control of bovine brucellosis Nepomuceno, Erivelton G. Barbosa, Alípio M. Silva, Marcos X. Perc, Matjaž R Soc Open Sci Engineering We present a theoretical approach to control bovine brucellosis. We have used individual-based modelling, which is a network-type alternative to compartmental models. Our model thus considers heterogeneous populations, and spatial aspects such as migration among herds and control actions described as pulse interventions are also easily implemented. We show that individual-based modelling reproduces the mean field behaviour of an equivalent compartmental model. Details of this process, as well as flowcharts, are provided to facilitate the reproduction of the presented results. We further investigate three numerical examples using real parameters of herds in the São Paulo state of Brazil, in scenarios which explore eradication, continuous and pulsed vaccination and meta-population effects. The obtained results are in good agreement with the expected behaviour of this disease, which ultimately showcases the effectiveness of our theory. The Royal Society Publishing 2018-05-02 /pmc/articles/PMC5990817/ /pubmed/29892455 http://dx.doi.org/10.1098/rsos.180200 Text en © 2018 The Authors. http://creativecommons.org/licenses/by/4.0/ Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.
spellingShingle Engineering
Nepomuceno, Erivelton G.
Barbosa, Alípio M.
Silva, Marcos X.
Perc, Matjaž
Individual-based modelling and control of bovine brucellosis
title Individual-based modelling and control of bovine brucellosis
title_full Individual-based modelling and control of bovine brucellosis
title_fullStr Individual-based modelling and control of bovine brucellosis
title_full_unstemmed Individual-based modelling and control of bovine brucellosis
title_short Individual-based modelling and control of bovine brucellosis
title_sort individual-based modelling and control of bovine brucellosis
topic Engineering
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5990817/
https://www.ncbi.nlm.nih.gov/pubmed/29892455
http://dx.doi.org/10.1098/rsos.180200
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