Epidemiology, Surveillance, and Prevention Strategies for Transboundary Animal Diseases

A special issue of Animals (ISSN 2076-2615). This special issue belongs to the section "Veterinary Clinical Studies".

Deadline for manuscript submissions: 31 March 2026 | Viewed by 713

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Guest Editor
Research Center for Veterinary Biosciences and Veterinary Public Health, Faculty of Veterinary Medicine, Chiang Mai University, Chiang Mai, Thailand
Interests: epidemiology; transboundary animal disease; spatial and prediction modelling
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Special Issue Information

Dear Colleagues,

Transboundary animal diseases such as African Swine Fever (ASF), Foot-and-Mouth Disease (FMD), Lumpy Skin Disease (LSD), and Avian Influenza (AI) continue to challenge animal health systems worldwide due to their rapid spread, significant economic burden, and capacity to disrupt trade, food security, and rural livelihoods. These diseases frequently cross-national borders through the movement of animals, vectors, and animal products, necessitating coordinated efforts across countries for effective control. A comprehensive understanding of the epidemiology of these diseases is critical for identifying transmission pathways, risk factors, and high-risk areas. Additionally, studies assessing the effectiveness of prevention and control measures, including vaccination, movement restrictions, and biosecurity practices, are essential for informing policy and guiding intervention strategies.

Researchers are encouraged to contribute studies that advance the understanding of the dynamics and key drivers of transboundary animal diseases. Contributions employing spatial analysis, mathematical modeling, simulation studies, risk identification, and risk mapping are particularly valuable for enhancing predictive capabilities and informing strategic planning. Submissions that examine the structure, efficiency, and timeliness of disease surveillance and reporting systems, as well as coordination mechanisms at both national and regional levels, are highly relevant for strengthening outbreak detection and response. Emphasis is placed on integrated, evidence-based approaches that support early detection, facilitate effective containment, and enhance long-term preparedness and control of these significant animal health threats.

Dr. Veerasak Punyapornwithaya
Guest Editor

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Keywords

  • transboundary animal diseases
  • epidemiology
  • disease outbreak reporting system
  • prevention
  • control strategy
  • key drivers of disease spreading
  • disease modelling
  • spatial and spatio-temporal analyses
  • disease transmission pathway
  • disease risk mapping
  • cross-border coordination

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Published Papers (1 paper)

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Research

18 pages, 2727 KB  
Article
Spatial Risk Distribution of Lumpy Skin Disease in Thailand Based on Maximum-Entropy Modeling
by Kusnul Yuli Maulana, Supitchaya Siriyakhun, Kannika Na-Lampang, Kannikar Intawong, Kenny Oriel A. Olana, Wengui Li, Maytawee Tamprateep and Veerasak Punyapornwithaya
Animals 2025, 15(16), 2456; https://doi.org/10.3390/ani15162456 - 21 Aug 2025
Viewed by 487
Abstract
Lumpy skin disease (LSD) poses a significant transboundary threat to livestock health and productivity, especially in regions where vector-borne transmission is a major driver of spread. Environmental and climatic factors are recognized as critical determinants of LSD transmission dynamics. This study aimed to [...] Read more.
Lumpy skin disease (LSD) poses a significant transboundary threat to livestock health and productivity, especially in regions where vector-borne transmission is a major driver of spread. Environmental and climatic factors are recognized as critical determinants of LSD transmission dynamics. This study aimed to model the environmental suitability for LSD across Thailand using a maximum-entropy approach. Outbreak data from 2021 to 2023 were analyzed alongside bioclimatic variables, land cover, normalized difference vegetation index (NDVI), and cattle population density. The model produced an area under the curve (AUC) value of 0.699 (~0.70), indicating moderate predictive performance. Based on variable contribution, land cover (65%), cattle density (25%), and NDVI (3%) were identified as the most influential predictors of environmental suitability for LSD. The resulting risk map identified central and northeastern Thailand as the most suitable regions for disease occurrence. These findings provide valuable insights to support risk-based surveillance, improve veterinary resource allocation, and enhance early warning systems for effective LSD prevention and control in Thailand. Full article
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