Spatial epidemiology of lumpy skin disease: unraveling patterns in dairy farm clusters with short interfarm proximity
Abstract Lumpy skin disease (LSD) has caused economic losses in cattle, and Thailand experienced a nationwide outbreak in 2021. Spatial epidemiology plays a crucial role in identifying transmission patterns and high-risk areas for targeted disease control. This study examines the spatial epidemiolog...
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| Language: | English |
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BMC
2025-06-01
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| Series: | Animal Diseases |
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| Online Access: | https://doi.org/10.1186/s44149-025-00177-8 |
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| author | Kusnul Yuli Maulana Supitchaya Srisawang Zailei Li Wengui Li Wittawat Modethed Veerasak Punyapornwithaya |
| author_facet | Kusnul Yuli Maulana Supitchaya Srisawang Zailei Li Wengui Li Wittawat Modethed Veerasak Punyapornwithaya |
| author_sort | Kusnul Yuli Maulana |
| collection | DOAJ |
| description | Abstract Lumpy skin disease (LSD) has caused economic losses in cattle, and Thailand experienced a nationwide outbreak in 2021. Spatial epidemiology plays a crucial role in identifying transmission patterns and high-risk areas for targeted disease control. This study examines the spatial epidemiology of LSD by analyzing clustering patterns, disease hotspots, and the directional spread of outbreaks in dairy farm networks with short interfarm proximities. LSD outbreak data from a large dairy farming area in northern Thailand were analyzed via multiple spatial analytical techniques. The standard deviation ellipse (SDE) approach, implemented with the Yuill and CrimeStat methods, was employed to determine the spatial-directional spread of outbreaks. Global and local Moran’s I statistics were used to assess spatial autocorrelation, whereas kernel density estimation (KDE) was used to identify the density areas of the LSD outbreaks. Ordinary kriging was applied to interpolate high-intensity surfaces. The results from the SDE indicate that the LSD outbreaks predominantly followed a northeast-to-southwest trend. Global Moran’s I revealed no statistical significance, whereas local Moran’s I indicated significant local spatial autocorrelation. KDE revealed a high density of outbreaks in the upper northern part of the farming region. Additionally, ordinary kriging was used to quantify the likelihood of outbreaks across different areas, highlighting potential high-intensity surfaces. These results enhance the understanding of LSD spatial epidemiology, providing valuable insights into disease dynamics and transmission. Additionally, these findings support policymakers in making informed decisions on targeted prevention, control strategies, and resource allocation at the local and regional levels. |
| format | Article |
| id | doaj-art-e5f1eec34467453ebe8deb12908b33c4 |
| institution | Kabale University |
| issn | 2731-0442 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | BMC |
| record_format | Article |
| series | Animal Diseases |
| spelling | doaj-art-e5f1eec34467453ebe8deb12908b33c42025-08-20T03:27:10ZengBMCAnimal Diseases2731-04422025-06-015111310.1186/s44149-025-00177-8Spatial epidemiology of lumpy skin disease: unraveling patterns in dairy farm clusters with short interfarm proximityKusnul Yuli Maulana0Supitchaya Srisawang1Zailei Li2Wengui Li3Wittawat Modethed4Veerasak Punyapornwithaya5Faculty of Veterinary Medicine, Chiang Mai UniversityResearch Center for Veterinary Biosciences and Veterinary Public Health, Faculty of Veterinary Medicine, Chiang Mai UniversityJoint International R&D Center of Veterinary Public Health, Yunnan Agricultural UniversityJoint International R&D Center of Veterinary Public Health, Yunnan Agricultural UniversityAnimal health development sector, Chiang Mai Provincial Livestock Office, Department of Livestock Development, Ministry of Agriculture and CooperativesFaculty of Veterinary Medicine, Chiang Mai UniversityAbstract Lumpy skin disease (LSD) has caused economic losses in cattle, and Thailand experienced a nationwide outbreak in 2021. Spatial epidemiology plays a crucial role in identifying transmission patterns and high-risk areas for targeted disease control. This study examines the spatial epidemiology of LSD by analyzing clustering patterns, disease hotspots, and the directional spread of outbreaks in dairy farm networks with short interfarm proximities. LSD outbreak data from a large dairy farming area in northern Thailand were analyzed via multiple spatial analytical techniques. The standard deviation ellipse (SDE) approach, implemented with the Yuill and CrimeStat methods, was employed to determine the spatial-directional spread of outbreaks. Global and local Moran’s I statistics were used to assess spatial autocorrelation, whereas kernel density estimation (KDE) was used to identify the density areas of the LSD outbreaks. Ordinary kriging was applied to interpolate high-intensity surfaces. The results from the SDE indicate that the LSD outbreaks predominantly followed a northeast-to-southwest trend. Global Moran’s I revealed no statistical significance, whereas local Moran’s I indicated significant local spatial autocorrelation. KDE revealed a high density of outbreaks in the upper northern part of the farming region. Additionally, ordinary kriging was used to quantify the likelihood of outbreaks across different areas, highlighting potential high-intensity surfaces. These results enhance the understanding of LSD spatial epidemiology, providing valuable insights into disease dynamics and transmission. Additionally, these findings support policymakers in making informed decisions on targeted prevention, control strategies, and resource allocation at the local and regional levels.https://doi.org/10.1186/s44149-025-00177-8ClusterHotspot areaLumpy skin diseaseSpatial epidemiology |
| spellingShingle | Kusnul Yuli Maulana Supitchaya Srisawang Zailei Li Wengui Li Wittawat Modethed Veerasak Punyapornwithaya Spatial epidemiology of lumpy skin disease: unraveling patterns in dairy farm clusters with short interfarm proximity Animal Diseases Cluster Hotspot area Lumpy skin disease Spatial epidemiology |
| title | Spatial epidemiology of lumpy skin disease: unraveling patterns in dairy farm clusters with short interfarm proximity |
| title_full | Spatial epidemiology of lumpy skin disease: unraveling patterns in dairy farm clusters with short interfarm proximity |
| title_fullStr | Spatial epidemiology of lumpy skin disease: unraveling patterns in dairy farm clusters with short interfarm proximity |
| title_full_unstemmed | Spatial epidemiology of lumpy skin disease: unraveling patterns in dairy farm clusters with short interfarm proximity |
| title_short | Spatial epidemiology of lumpy skin disease: unraveling patterns in dairy farm clusters with short interfarm proximity |
| title_sort | spatial epidemiology of lumpy skin disease unraveling patterns in dairy farm clusters with short interfarm proximity |
| topic | Cluster Hotspot area Lumpy skin disease Spatial epidemiology |
| url | https://doi.org/10.1186/s44149-025-00177-8 |
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