Spatiotemporal analysis of equine infectious anemia and prediction of risk areas in Europe.
Abstract: Equine Infectious Anemia (EIA) is a vector-borne persistent viral infection in equine animals. The EIA is characterized by recurrent fever, thrombocytopenia, depression, anemia, rapid weight loss, and lower body edema. Control of EIA is achieved through the elimination or isolation of infected animals, resulting in significant economic losses. In recent years, many countries in Europe have experienced outbreaks of EIA, which could potentially develop into a new wave of epidemic and pose a significant threat to the healthy development of the equine industry. This study utilized spatiotemporal analysis techniques and ecological niche modeling to investigate the spatiotemporal distribution characteristics of historical EIA outbreaks and predict risk areas for EIA occurrence in Europe. Spatiotemporal analysis results indicate that from 2005 to 2023, the EIA outbreaks in Europe exhibit five significant spatiotemporal clusters, with hotspots concentrated in southeastern France and northwestern Italy. Ecological niche modeling reveals that western, central, and southern Europe are high-risk areas for EIA outbreaks. Annual mean temperature, annual precipitation, and horse density are important variables that influence the occurrence of EIA. The results of this study can provide decision-makers with valuable insights, helping with EIA monitoring and resource allocation.
Copyright © 2024 Elsevier B.V. All rights reserved.
Publication Date: 2024-07-08 PubMed ID: 38986294DOI: 10.1016/j.prevetmed.2024.106281Google Scholar: Lookup
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Summary
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This research involves studying the historical patterns of Equine Infectious Anemia (EIA) outbreaks in Europe, and making predictions about future risk areas using spatiotemporal analysis and ecological niche modeling methods.
Spatiotemporal Analysis of EIA Outbreaks
- The research begins with a spatiotemporal investigation of previous EIA outbreaks in Europe, from 2005 to 2023. This type of analysis uses both spatial and temporal data to understand geographic variation over time.
- The spatiotemporal analysis identified five significant clusters of EIA outbreaks, primarily centered in southeastern France and northwestern Italy. These ‘hotspots’ indicate areas where EIA has been most prevalent in the past.
Ecological Niche Modeling for Future Predictions
- Next, the research employs ecological niche modeling, a technique for predicting the distribution of species or diseases based on environmental and ecological factors.
- This modeling reveals that western, central, and southern Europe are potential high-risk areas for future EIA outbreaks based on current environmental conditions and horse populations.
- Key variables impacting the occurrence of EIA include annual mean temperature, annual precipitation, and horse density. This information suggests that certain environmental conditions and high horse populations can create a suitable ‘niche’ for EIA to occur.
Implications of the Study
- This research offers valuable insights that can aid decision-makers involved in the management and control of EIA. By understanding where and when outbreaks are likely to occur, resources for prevention and treatment can be allocated more effectively.
- While the control of EIA is usually achieved through isolating or eliminating infected animals, this causes significant economic loss; early identification of risk areas may help mitigate this.
- Given the recent EIA outbreaks across Europe, this study has the potential to help prevent a widespread epidemic, protecting the equine industry’s health and sustainability.
Cite This Article
APA
An Q, Li Y, Sun Z, Gao X, Wang H.
(2024).
Spatiotemporal analysis of equine infectious anemia and prediction of risk areas in Europe.
Prev Vet Med, 230, 106281.
https://doi.org/10.1016/j.prevetmed.2024.106281 Publication
Researcher Affiliations
- College of Veterinary Medicine, Northeast Agricultural University, Harbin, People's Republic of China; Key Laboratory of the Provincial Education Department of Heilongjiang for Common Animal Disease Prevention and Treatment, College of Veterinary Medicine, Northeast Agricultural University, Harbin, People's Republic of China. Electronic address: aq_1998@126.com.
- College of Veterinary Medicine, Northeast Agricultural University, Harbin, People's Republic of China; Key Laboratory of the Provincial Education Department of Heilongjiang for Common Animal Disease Prevention and Treatment, College of Veterinary Medicine, Northeast Agricultural University, Harbin, People's Republic of China. Electronic address: yuepeng_lii@126.com.
- College of Veterinary Medicine, Northeast Agricultural University, Harbin, People's Republic of China; Key Laboratory of the Provincial Education Department of Heilongjiang for Common Animal Disease Prevention and Treatment, College of Veterinary Medicine, Northeast Agricultural University, Harbin, People's Republic of China. Electronic address: 1010470957@qq.com.
- College of Veterinary Medicine, Northeast Agricultural University, Harbin, People's Republic of China; Key Laboratory of the Provincial Education Department of Heilongjiang for Common Animal Disease Prevention and Treatment, College of Veterinary Medicine, Northeast Agricultural University, Harbin, People's Republic of China. Electronic address: gam2006gx@126.com.
- College of Veterinary Medicine, Northeast Agricultural University, Harbin, People's Republic of China; Key Laboratory of the Provincial Education Department of Heilongjiang for Common Animal Disease Prevention and Treatment, College of Veterinary Medicine, Northeast Agricultural University, Harbin, People's Republic of China. Electronic address: hbwang1940@neau.edu.cn.
Conflict of Interest Statement
Declaration of Competing Interest The authors declare that there is no conflict of interest.
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