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Farm management practices, biosecurity and influenza a virus detection in swine farms: a comprehensive study in colombia

Biosecurity protocols (BP) and good management practices are key to reduce the risk of introduction and transmission of infectious diseases into the pig farms. In this observational cross-sectional study, survey data were collected from 176 pig farms with inventories over 100 sows in Colombia. We an...

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Autores principales: Karl, Ciuoderis-Aponte, Andres, Diaz, Carlos, Muskus, Peña, Mario, Juan, Hernández-Ortiz, Jorge, Osorio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9532805/
https://www.ncbi.nlm.nih.gov/pubmed/36199147
http://dx.doi.org/10.1186/s40813-022-00287-6
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author Karl, Ciuoderis-Aponte
Andres, Diaz
Carlos, Muskus
Peña, Mario
Juan, Hernández-Ortiz
Jorge, Osorio
author_facet Karl, Ciuoderis-Aponte
Andres, Diaz
Carlos, Muskus
Peña, Mario
Juan, Hernández-Ortiz
Jorge, Osorio
author_sort Karl, Ciuoderis-Aponte
collection PubMed
description Biosecurity protocols (BP) and good management practices are key to reduce the risk of introduction and transmission of infectious diseases into the pig farms. In this observational cross-sectional study, survey data were collected from 176 pig farms with inventories over 100 sows in Colombia. We analyzed a complex survey dataset to explore the structure and identify clustering patterns using Multiple Correspondence Analysis (MCA) of swine farms in Colombia, and estimated its association with Influenza A virus detection. Two principal dimensions contributed to 27.6% of the dataset variation. Farms with highest contribution to dimension 1 were larger farrow-to-finish farms, using self-replacement of gilts and implementing most of the measures evaluated. In contrast, farms with highest contribution to dimension 2 were medium to large farrow-to-finish farms, but implemented biosecurity in a lower degree. Additionally, two farm clusters were identified by Hierarchical Cluster Analysis (HCA), and the odds of influenza A virus detection was statistically different between clusters (OR 7.29, CI: 1.7,66, p = < 0.01). Moreover, after logistic regression analysis, three important variables were associated with higher odds of influenza detection: (1) “location in an area with a high density of pigs”, (2) “farm size”, and (3) “after cleaning and disinfecting, the facilities are allowed to dry before use”. Our results revealed two clustering patterns of swine farms. This systematic analysis of complex survey data identified relationships between biosecurity, husbandry practices and influenza status. This approach helped to identify gaps on biosecurity and key elements for designing successful strategies to prevent and control swine respiratory diseases in the swine industry. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40813-022-00287-6.
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spelling pubmed-95328052022-10-05 Farm management practices, biosecurity and influenza a virus detection in swine farms: a comprehensive study in colombia Karl, Ciuoderis-Aponte Andres, Diaz Carlos, Muskus Peña, Mario Juan, Hernández-Ortiz Jorge, Osorio Porcine Health Manag Research Biosecurity protocols (BP) and good management practices are key to reduce the risk of introduction and transmission of infectious diseases into the pig farms. In this observational cross-sectional study, survey data were collected from 176 pig farms with inventories over 100 sows in Colombia. We analyzed a complex survey dataset to explore the structure and identify clustering patterns using Multiple Correspondence Analysis (MCA) of swine farms in Colombia, and estimated its association with Influenza A virus detection. Two principal dimensions contributed to 27.6% of the dataset variation. Farms with highest contribution to dimension 1 were larger farrow-to-finish farms, using self-replacement of gilts and implementing most of the measures evaluated. In contrast, farms with highest contribution to dimension 2 were medium to large farrow-to-finish farms, but implemented biosecurity in a lower degree. Additionally, two farm clusters were identified by Hierarchical Cluster Analysis (HCA), and the odds of influenza A virus detection was statistically different between clusters (OR 7.29, CI: 1.7,66, p = < 0.01). Moreover, after logistic regression analysis, three important variables were associated with higher odds of influenza detection: (1) “location in an area with a high density of pigs”, (2) “farm size”, and (3) “after cleaning and disinfecting, the facilities are allowed to dry before use”. Our results revealed two clustering patterns of swine farms. This systematic analysis of complex survey data identified relationships between biosecurity, husbandry practices and influenza status. This approach helped to identify gaps on biosecurity and key elements for designing successful strategies to prevent and control swine respiratory diseases in the swine industry. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40813-022-00287-6. BioMed Central 2022-10-05 /pmc/articles/PMC9532805/ /pubmed/36199147 http://dx.doi.org/10.1186/s40813-022-00287-6 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Karl, Ciuoderis-Aponte
Andres, Diaz
Carlos, Muskus
Peña, Mario
Juan, Hernández-Ortiz
Jorge, Osorio
Farm management practices, biosecurity and influenza a virus detection in swine farms: a comprehensive study in colombia
title Farm management practices, biosecurity and influenza a virus detection in swine farms: a comprehensive study in colombia
title_full Farm management practices, biosecurity and influenza a virus detection in swine farms: a comprehensive study in colombia
title_fullStr Farm management practices, biosecurity and influenza a virus detection in swine farms: a comprehensive study in colombia
title_full_unstemmed Farm management practices, biosecurity and influenza a virus detection in swine farms: a comprehensive study in colombia
title_short Farm management practices, biosecurity and influenza a virus detection in swine farms: a comprehensive study in colombia
title_sort farm management practices, biosecurity and influenza a virus detection in swine farms: a comprehensive study in colombia
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9532805/
https://www.ncbi.nlm.nih.gov/pubmed/36199147
http://dx.doi.org/10.1186/s40813-022-00287-6
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