Por favor, use este identificador para citar o enlazar este ítem: https://hdl.handle.net/10495/43918
Título : Farm management practices, biosecurity and influenza a virus detection in swine farms: a comprehensive study in Colombia
Autor : Muskus López, Carlos Enrique
Díaz, Andrés
Ciuoderis Aponte, Karl
Peña, Mario
Hernández Ortiz, Juan
Osorio, Jorge
metadata.dc.subject.*: Epidemiología
Epidemiology
Enfermedades Transmisibles
Communicable Diseases
Virus de la Influenza A
Influenza A virus
Teorema de Bayes
Bayes Theorem
Cerdo
Swine
Granjas porcinas
Swine farms
http://aims.fao.org/aos/agrovoc/c_7555
https://id.nlm.nih.gov/mesh/D004813
https://id.nlm.nih.gov/mesh/D003141
https://id.nlm.nih.gov/mesh/D009980
https://id.nlm.nih.gov/mesh/D001499
Fecha de publicación : 2022
Editorial : BioMed Central
Citación : Ciuoderis-Aponte, K., Diaz, A., Muskus, C. et al. Farm management practices, biosecurity and influenza a virus detection in swine farms: a comprehensive study in Colombia. Porc Health Manag 8, 42 (2022). https://doi.org/10.1186/s40813-022-00287-6
Resumen : ABSTRACT: 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.
ISSN : 2055-5660
metadata.dc.identifier.doi: 10.1186/s40813-022-00287-6
Aparece en las colecciones: Artículos de Revista en Ciencias Médicas

Ficheros en este ítem:
Fichero Descripción Tamaño Formato  
MuskusCarlos_2022_Influenza_Pathogen_Farms.pdfArtículo de investigación1.15 MBAdobe PDFVisualizar/Abrir


Este ítem está sujeto a una licencia Creative Commons Licencia Creative Commons Creative Commons