Ciuoderis-Aponte Karl, Diaz Andres, Muskus Carlos, Peña Mario, Hernández-Ortiz Juan, Osorio Jorge
Universidad Nacional de Colombia sede Medellín. Consortium Colombia Wisconsin One Health, Cra 75#61-85, 050034, Medellín, Colombia.
Pig Improvement Company, Querato, Mexico.
Porcine Health Manag. 2022 Oct 5;8(1):42. doi: 10.1186/s40813-022-00287-6.
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.
生物安全协议(BP)和良好的管理实践是降低传染病传入和传播到猪场风险的关键。在这项观察性横断面研究中,从哥伦比亚176个存栏母猪超过100头的猪场收集了调查数据。我们分析了一个复杂的调查数据集,使用哥伦比亚猪场的多重对应分析(MCA)来探索结构并识别聚类模式,并估计其与甲型流感病毒检测的关联。两个主要维度贡献了数据集变异的27.6%。对维度1贡献最大的猪场是规模较大的从产仔到育肥一体化猪场,使用后备母猪自繁并实施了大部分评估措施。相比之下,对维度2贡献最大的猪场是中型到大型的从产仔到育肥一体化猪场,但生物安全实施程度较低。此外,通过层次聚类分析(HCA)识别出两个猪场集群,集群之间甲型流感病毒检测的几率在统计学上存在差异(OR 7.29,CI:1.7,66,p = < 0.01)。此外,经过逻辑回归分析,三个重要变量与流感检测几率较高相关:(1)“位于猪高密度区域”,(2)“猪场规模”,以及(3)“清洁和消毒后,设施在使用前允许干燥”。我们的结果揭示了猪场的两种聚类模式。这种对复杂调查数据的系统分析确定了生物安全、饲养管理实践与流感状况之间的关系。这种方法有助于识别生物安全方面的差距以及设计成功的猪业预防和控制猪呼吸道疾病策略的关键要素。