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调查亚洲牛结节性皮肤病(LSD)疫情的跨境传播模式和聚集特征:利用疫情数据(2019 - 2023年)支持牛结节性皮肤病防控策略

Investigating Transboundary Spread Patterns and Cluster Characteristics of Lumpy Skin Disease (LSD) Outbreaks in Asia: Levering the Outbreak Data (2019-2023) to Support the LSD Prevention and Control Strategies.

作者信息

Punyapornwithaya Veerasak, Srisawang Supitchaya, Arjkumpa Orapun, Phimpraphai Waraphon, Buamithup Noppawan, Purevsuren Bolortuya, Rinzin Karma, Abila Ronello, Sutar Ashish

机构信息

Research Center for Veterinary Biosciences and Veterinary Public Health, Faculty of Veterinary Medicine, Chiang Mai University, Chiang Mai 50100, Thailand.

Animal Health Section of the 4th Regional Livestock Office, Department of Livestock Development, Ministry of Agriculture and Cooperatives, Khon Kaen 40260, Thailand.

出版信息

Transbound Emerg Dis. 2025 Aug 6;2025:2964021. doi: 10.1155/tbed/2964021. eCollection 2025.

Abstract

Lumpy skin disease (LSD) has rapidly spread across Asia, posing significant threats to livestock industries. This study aims to examine the spatial directional trends and spatiotemporal clusters of LSD outbreaks in South, East, and Southeast Asia from January 2019 to December 2023. Official LSD outbreak data were analyzed using spatial and spatiotemporal models. The standard deviational ellipse (SDE) method was applied to assess directional distribution trends, while space-time permutation (STP) and space-time Poisson models were utilized to identify outbreak clusters. A total of 1385 LSD outbreaks were recorded in the study region during the period. In the Asia region, the directional analysis of all outbreaks revealed trends from the south to the southeast and from the northeast to the southeast, based on the SDE case-weighted and SDE case-unweighted approaches, respectively. Additionally, distinct directional patterns were identified for each subregion. A comparison of the space-time Poisson and STP models showed variations in cluster locations and sizes. The STP model identified primary clusters in India, Bhutan, the Republic of Korea, and Vietnam, whereas the space-time Poisson model highlighted primary clusters in India, Thailand, and Mongolia. Both models detected secondary clusters in various countries including India, Pakistan, Bhutan, China, Mongolia, Nepal, Cambodia, Vietnam, Thailand, Indonesia, Malaysia, Singapore, Sri Lanka, and the Republic of Korea, with the space-time Poisson model identifying larger cluster sizes and the STP model capturing more localized clusters. These findings provide valuable insights into the spatial and temporal dynamics of LSD outbreaks in Asia. The results of this study contribute to a better understanding of LSD epidemiology and offer essential information to support the development of regional and subregional prevention and control strategies.

摘要

结节性皮肤病(LSD)已在亚洲迅速蔓延,对畜牧业构成重大威胁。本研究旨在考察2019年1月至2023年12月期间南亚、东亚和东南亚地区LSD疫情的空间方向趋势和时空聚集情况。利用空间和时空模型对官方LSD疫情数据进行了分析。应用标准偏离椭圆(SDE)方法评估方向分布趋势,同时利用时空置换(STP)和时空泊松模型识别疫情聚集区。在此期间,研究区域共记录了1385起LSD疫情。在亚洲区域,基于SDE病例加权法和SDE病例未加权法,对所有疫情的方向分析分别显示出从南到东南以及从东北到东南的趋势。此外,还为每个次区域确定了不同的方向模式。时空泊松模型和STP模型的比较显示了聚集区位置和大小的差异。STP模型确定印度、不丹、韩国和越南为主要聚集区,而时空泊松模型则突出了印度、泰国和蒙古的主要聚集区。两个模型均在包括印度、巴基斯坦、不丹、中国、蒙古、尼泊尔、柬埔寨、越南、泰国、印度尼西亚、马来西亚、新加坡、斯里兰卡和韩国在内的多个国家检测到了次要聚集区,其中时空泊松模型识别出的聚集区规模更大,而STP模型捕捉到的聚集区更具局部性。这些发现为亚洲LSD疫情的时空动态提供了有价值的见解。本研究结果有助于更好地理解LSD流行病学,并为制定区域和次区域预防控制策略提供重要信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/69ab/12349989/5d2b89ccd03b/TBED2025-2964021.001.jpg

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