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Structural equation models to estimate risk of infection and tolerance to bovine mastitis

BACKGROUND: One method to improve durably animal welfare is to select, as reproducers, animals with the highest ability to resist or tolerate infection. To do so, it is necessary to distinguish direct and indirect mechanisms of resistance and tolerance because selection on these traits is believed t...

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Autores principales: Detilleux, Johann, Theron, Léonard, Duprez, Jean-Noël, Reding, Edouard, Humblet, Marie-France, Planchon, Viviane, Delfosse, Camille, Bertozzi, Carlo, Mainil, Jacques, Hanzen, Christian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3626708/
https://www.ncbi.nlm.nih.gov/pubmed/23496993
http://dx.doi.org/10.1186/1297-9686-45-6
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author Detilleux, Johann
Theron, Léonard
Duprez, Jean-Noël
Reding, Edouard
Humblet, Marie-France
Planchon, Viviane
Delfosse, Camille
Bertozzi, Carlo
Mainil, Jacques
Hanzen, Christian
author_facet Detilleux, Johann
Theron, Léonard
Duprez, Jean-Noël
Reding, Edouard
Humblet, Marie-France
Planchon, Viviane
Delfosse, Camille
Bertozzi, Carlo
Mainil, Jacques
Hanzen, Christian
author_sort Detilleux, Johann
collection PubMed
description BACKGROUND: One method to improve durably animal welfare is to select, as reproducers, animals with the highest ability to resist or tolerate infection. To do so, it is necessary to distinguish direct and indirect mechanisms of resistance and tolerance because selection on these traits is believed to have different epidemiological and evolutionary consequences. METHODS: We propose structural equation models with latent variables (1) to quantify the latent risk of infection and to identify, among the many potential mediators of infection, the few ones that influence it significantly and (2) to estimate direct and indirect levels of tolerance of animals infected naturally with pathogens. We applied the method to two surveys of bovine mastitis in the Walloon region of Belgium, in which we recorded herd management practices, mastitis frequency, and results of bacteriological analyses of milk samples. RESULTS AND DISCUSSION: Structural equation models suggested that, among more than 35 surveyed herd characteristics, only nine (age, addition of urea in the rations, treatment of subclinical mastitis, presence of dirty liner, cows with hyperkeratotic teats, machine stripping, pre- and post-milking teat disinfection, and housing of milking cows in cubicles) were directly and significantly related to a latent measure of bovine mastitis, and that treatment of subclinical mastitis was involved in the pathway between post-milking teat disinfection and latent mastitis. These models also allowed the separation of direct and indirect effects of bacterial infection on milk productivity. Results suggested that infected cows were tolerant but not resistant to mastitis pathogens. CONCLUSIONS: We revealed the advantages of structural equation models, compared to classical models, for dissecting measurements of resistance and tolerance to infectious diseases, here bovine mastitis. Using our method, we identified nine major risk factors that were directly associated with an increased risk of mastitis and suggested that cows were tolerant but not resistant to mastitis. Selection should aim at improved resistance to infection by mastitis pathogens, although further investigations are needed due to the limitations of the data used in this study.
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spelling pubmed-36267082013-04-24 Structural equation models to estimate risk of infection and tolerance to bovine mastitis Detilleux, Johann Theron, Léonard Duprez, Jean-Noël Reding, Edouard Humblet, Marie-France Planchon, Viviane Delfosse, Camille Bertozzi, Carlo Mainil, Jacques Hanzen, Christian Genet Sel Evol Research BACKGROUND: One method to improve durably animal welfare is to select, as reproducers, animals with the highest ability to resist or tolerate infection. To do so, it is necessary to distinguish direct and indirect mechanisms of resistance and tolerance because selection on these traits is believed to have different epidemiological and evolutionary consequences. METHODS: We propose structural equation models with latent variables (1) to quantify the latent risk of infection and to identify, among the many potential mediators of infection, the few ones that influence it significantly and (2) to estimate direct and indirect levels of tolerance of animals infected naturally with pathogens. We applied the method to two surveys of bovine mastitis in the Walloon region of Belgium, in which we recorded herd management practices, mastitis frequency, and results of bacteriological analyses of milk samples. RESULTS AND DISCUSSION: Structural equation models suggested that, among more than 35 surveyed herd characteristics, only nine (age, addition of urea in the rations, treatment of subclinical mastitis, presence of dirty liner, cows with hyperkeratotic teats, machine stripping, pre- and post-milking teat disinfection, and housing of milking cows in cubicles) were directly and significantly related to a latent measure of bovine mastitis, and that treatment of subclinical mastitis was involved in the pathway between post-milking teat disinfection and latent mastitis. These models also allowed the separation of direct and indirect effects of bacterial infection on milk productivity. Results suggested that infected cows were tolerant but not resistant to mastitis pathogens. CONCLUSIONS: We revealed the advantages of structural equation models, compared to classical models, for dissecting measurements of resistance and tolerance to infectious diseases, here bovine mastitis. Using our method, we identified nine major risk factors that were directly associated with an increased risk of mastitis and suggested that cows were tolerant but not resistant to mastitis. Selection should aim at improved resistance to infection by mastitis pathogens, although further investigations are needed due to the limitations of the data used in this study. BioMed Central 2013-03-06 /pmc/articles/PMC3626708/ /pubmed/23496993 http://dx.doi.org/10.1186/1297-9686-45-6 Text en Copyright © 2012 Detilleux et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research
Detilleux, Johann
Theron, Léonard
Duprez, Jean-Noël
Reding, Edouard
Humblet, Marie-France
Planchon, Viviane
Delfosse, Camille
Bertozzi, Carlo
Mainil, Jacques
Hanzen, Christian
Structural equation models to estimate risk of infection and tolerance to bovine mastitis
title Structural equation models to estimate risk of infection and tolerance to bovine mastitis
title_full Structural equation models to estimate risk of infection and tolerance to bovine mastitis
title_fullStr Structural equation models to estimate risk of infection and tolerance to bovine mastitis
title_full_unstemmed Structural equation models to estimate risk of infection and tolerance to bovine mastitis
title_short Structural equation models to estimate risk of infection and tolerance to bovine mastitis
title_sort structural equation models to estimate risk of infection and tolerance to bovine mastitis
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3626708/
https://www.ncbi.nlm.nih.gov/pubmed/23496993
http://dx.doi.org/10.1186/1297-9686-45-6
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