Several outbreaks of highly pathogenic avian influenza (HPAI) in poultry have already been documented across the world, causing major economic losses. Research on diverse perspectives for future HPAI outbreaks’ prevention is desperately needed. It is critical to determine high-risk areas for HPAI outbreaks in order to develop high-level biosecurity in all such areas. The aim of this study is to identify high-risk areas as hotspots for high rates of birds’ infection and mortality and culling. We used “hierarchical clustering on principal components” (HCPC) to classify infected poultry farms in South Korea based on the point prevalence rate, infections, and deaths in susceptible birds. The linear combination of the original predictors was determined using “principal component analysis (PCA)”. Based on PCA, we applied the hierarchical clustering algorithm, which divided the data into four clusters based on the dissimilarity matrix. These four groups of poultry farms were identified on the basis of five variables. According to the findings based on the HCPC method, poultry farms in “cluster 4” had significantly higher average bird infections with high mortality when compared to other clusters. Similarly, the poultry farms in “cluster 2” had robust average bird culling in place to limit bird infectivity and mortality due to a high number of susceptible birds. The poultry farms belonging to “cluster 3” had a significantly higher average point prevalence rate of HPAI H5N6 cases than the rest of the clusters. Based on this study, it is recommended that poultry farms with a high number of infections and mortality in susceptible birds should implement proper biosecurity management to control HPAI infections while avoiding the culling of a large number of birds.
Background Since 2003, the H5 highly pathogenic avian influenza (HPAI) subtype has caused massive economic losses in the poultry industry in South Korea. The role of inland water bodies in avian influenza (AI) outbreaks has not been investigated. Identifying water bodies that facilitate risk pathways leading to the incursion of the HPAI virus (HPAIV) into poultry farms is essential for implementing specific precautionary measures to prevent viral transmission. Objectives This matched case-control study (1:4) examined whether inland waters were associated with a higher risk of AI outbreaks in the neighboring poultry farms. Methods Rivers, irrigation canals, lakes, and ponds were considered inland water bodies. The cases and controls were chosen based on the matching criteria. The nearest possible farms located within a radius of 3 km of the case farms were chosen as the control farms. The poultry farms were selected randomly, and two HPAI epidemics (H5N8 [2014–2016] and H5N6 [2016–2017]) were studied. Conditional logistic regression analysis was applied. Results Statistical analysis revealed that inland waters near poultry farms were significant risk factors for AI outbreaks. The study speculated that freely wandering wild waterfowl and small animals contaminate areas surrounding poultry farms. Conclusions Pet birds and animals raised alongside poultry birds on farm premises may wander easily to nearby waters, potentially increasing the risk of AI infection in poultry farms. Mechanical transmission of the AI virus occurs when poultry farm workers or visitors come into contact with infected water bodies or their surroundings. To prevent AI outbreaks in the future, poultry farms should adopt strict precautions to avoid contact with nearby water bodies and their surroundings.
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