ArticleTransboundary and emerging diseases2023
Risk Factors and Spatiotemporal Distribution of Lumpy Skin Disease Occurrence in the Asian Continent during 2012-2022: An Ecological Niche Model.
Article in Transboundary and emerging diseases, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Lumpy Skin Disease in Cattle and Buffalo in Asian Countries: A Systematic Review and Meta-Analysis.Veterinary medicine and science · 2025Pooled it
- Climate-driven shifts in lumpy skin disease risk across Iran: Insights from ensemble species distribution models.One health (Amsterdam, Netherlands) · 2026Article
- Windborne Dispersal of Arthropod Vectors as a Pathway for Lumpy Skin Disease Virus Introduction into South Korea: A Multi-Species, Source-Attributed Modelling Study.Animals : an open access journal from MDPI · 2026Article
- Article
- The global scenario of lumpy skin disease, its epidemiological investigation, and prevalence in livestock: A review.Veterinary and animal science · 2026Review
- Spatial epidemiology of lumpy skin disease outbreaks in Thailand: proximity patterns, case concentrations, spatio-temporal clusters, and interpolated case distribution.Frontiers in veterinary science · 2026Article
- Global foot-and-mouth disease risk assessment based on multiple spatial analysis and ecological niche model.The veterinary quarterly · 2025Article
- Article
- Genetic Characterization of the First Case of Lumpy Skin Disease in Singapore, 2022.Veterinary sciences · 2025Article
- Spatial Risk Distribution of Lumpy Skin Disease in Thailand Based on Maximum-Entropy Modeling.Animals : an open access journal from MDPI · 2025Article
- Article
- Lumpy skin disease: A growing threat to the global livestock industry.Open veterinary journal · 2025Review
- Geographical Distribution, Spatial Directional Trends, and Spatio-Temporal Clusters of the First Rapid and Widespread Lumpy Skin Disease Outbreaks in Thailand.Transboundary and emerging diseases · 2025Article
- Spatiotemporal Distribution and Meteorological Determinants of Lumpy Skin Disease (LSD) Occurrence in Bangladesh From 2020 to 2023.Transboundary and emerging diseases · 2025Article
- 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.Transboundary and emerging diseases · 2025Article
- Lumpy skin disease diagnosis in cattle: A deep learning approach optimized with RMSProp and MobileNetV2.PloS one · 2024Article
- Estimating the Transmission Kernel for Lumpy Skin Disease Virus from Data on Outbreaks in Thailand in 2021.Viruses · 2023Article
- Review
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Lumpy skin disease (LSD) is an emerging transboundary infectious disease of animals with high morbidity and low mortality rates. The infection occurs in cattle, buffalo, and some closely related wild animals, with cattle and buffalo showing higher susceptibility than other species. The primary mode of disease transmission is the mechanical dispersion of bloodsucking insects. The disease symptoms, including animal fur damage, weight loss, decline in milk production, infertility, and miscarriage, lead to huge economic losses in regions and countries with LSD outbreaks. The present study aimed to analyze the incidence data of LSD in the Asian continent from January 2012 to September 2022, identify spatiotemporal clusters and risk factors of the disease, and establish a maximum entropy ecological niche model to predict high-risk areas for disease outbreaks. The studied variables included bioclimatic factors, land type, and population density. Following the screening process, 12 variables were included in the maximum entropy model. Among them, the variable contribution rates of cattle density, land cover, isothermality, buffalo density, and maximum temperature of the warmest month were 53.8%, 10.9%, 9.2%, 8.9%, and 8%, respectively. Accounting for more than 90% of the total variable contribution rate, these five variables were considered to be the important influencing factors of LSD outbreaks. According to the results, nine spatiotemporal clusters approximately matched the high-risk areas predicted by the model. The Caucasus region of Russia; the Russian border areas of Kazakhstan, Turkey, Syria, Lebanon, Palestine, and Israel; and the western regions of Iran, India, and Southeast Asia were predicted to be high-risk areas. Thus, this study provides the spatiotemporal clusters, risk factors, and high-risk areas of LSD outbreaks in the Asian continent, which can help formulate more effective disease prevention and control policies.
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