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Home / Equine Research Bank / Transbound Emerg Dis / Environmental and Historical Determinants of African Horse S...
Transboundary and emerging diseases2024; 2024; 5586647; doi: 10.1155/2024/5586647

Environmental and Historical Determinants of African Horse Sickness: Insights from Predictive Modeling.

Abstract: African horse sickness (AHS) is a viral disease transmitted by arthropods that impacts Equidae, specifically horses and related species. Recognized as a notifiable disease by the World Organisation for Animal Health (WOAH), AHS is associated with a high mortality rate of 80%-90% in susceptible hosts and exhibits rapid transmission dynamics. Historical records document numerous instances of mass horse deaths attributed to AHS, with recent occurrences in Thailand and Malaysia in 2020 causing heightened concerns within the local horse industry. The lack of a comprehensive global perspective on the distribution and transmission of AHS poses challenges in comprehending and implementing effective prevention and control strategies. This study marks a pioneering effort in analyzing the global epidemiological patterns of AHS across different regions. By employing predictive modeling with a comprehensive set of environmental variables, we uncovered overarching global patterns in AHS dynamics, a first in this field. Our analysis revealed significant regional differences influenced by specific climatic conditions, highlighting the disease's complexity. The study also identifies new high-risk areas for AHS, underscoring the necessity for regionally tailored disease management strategies. Despite some limitations, such as the exclusion of wild equine data, this research offers critical insights for global AHS intervention and prevention, setting a path for future research incorporating broader datasets and socioeconomic factors.
Copyright © 2024 KwangHyok Kim et al.
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Publication Date: 2024-08-13 PubMed ID: 40303017PubMed Central: PMC12017013DOI: 10.1155/2024/5586647Google Scholar: Lookup
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Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

Overview

  • This research investigates the global spread and risk factors of African horse sickness (AHS), a deadly viral disease affecting horses and related species.
  • By using predictive modeling and environmental data, the study identifies key drivers of AHS outbreaks and highlights new high-risk regions, aiming to improve disease prevention and control worldwide.

Background and Importance of Study

  • African Horse Sickness (AHS): AHS is a viral disease transmitted primarily through arthropod vectors, notably certain species of midges (Culicoides), affecting Equidae such as horses, donkeys, and zebras.
  • Severity: The disease has a very high mortality rate in susceptible animals, typically between 80% to 90%, making it a significant concern for equine health and industries.
  • Historical Impact: Numerous historic outbreaks have recorded large-scale horse casualties, affecting equine populations and economies.
  • Recent Events: Recent outbreaks in countries such as Thailand and Malaysia (in 2020) spotlight ongoing risks outside traditional endemic zones, raising international alarms.
  • Global Challenge: Prior to this study, there was no comprehensive, global-scale understanding of where and why AHS occurs, limiting international disease control efforts.

Research Goals and Approach

  • Objective: To analyze and model the global epidemiological patterns of AHS across various regions, and understand the environmental and historical factors driving outbreaks.
  • Predictive Modeling: The study utilized predictive models incorporating a diverse set of environmental variables such as climate data (temperature, precipitation), ecological factors, and historical outbreak records.
  • Data Sources: The model relied on reported outbreaks, environmental datasets, and global geographical distributions to identify disease risk patterns.

Key Findings

  • Global Patterns: For the first time, the study uncovers broad global trends in AHS occurrence, showing that the disease dynamics vary significantly by region.
  • Regional Differences: Climatic conditions such as temperature, humidity, and rainfall strongly influence habitat suitability for the vector species and virus survival, resulting in distinct regional risk profiles.
  • Identification of New High-Risk Areas: The model highlights previously under-recognized geographic zones that may be vulnerable to AHS outbreaks, possibly due to climate change or changes in animal trade and movement.
  • Disease Complexity: The interplay between environmental factors and historical transmission patterns contributes to the complex nature of the disease’s spread and persistence.

Limitations

  • Wild Equine Data Exclusion: The study did not include data related to wild equine populations, which could influence the understanding of AHS reservoirs and transmission dynamics in nature.
  • Simplified Socioeconomic Factors: Socioeconomic and anthropogenic factors such as animal trade, veterinary infrastructure, and local control measures were not incorporated, which can impact disease spread and control success.
  • Data Gaps: Potential underreporting in some regions may affect model accuracy and completeness.

Implications and Future Directions

  • Disease Management: Insights from the study encourage development of region-specific control strategies tailored to local environmental and epidemiological contexts.
  • Policy and Surveillance: Policymakers and animal health authorities can use the risk maps and findings to enhance surveillance and preparedness, focusing on emerging high-risk zones.
  • Extended Research: Future research should incorporate wild equine data and socioeconomic variables to refine predictive models and better capture the multifaceted nature of AHS transmission.
  • Global Collaboration: Coordinated international efforts will be necessary to monitor and control AHS, especially as environmental changes alter disease distributions.

Cite This Article

APA
Kim K, Xu T, Kannan Villalan A, Chi T, Yu X, Jin M, Wu R, Ni G, Sui S, Wang Z, Wang X. (2024). Environmental and Historical Determinants of African Horse Sickness: Insights from Predictive Modeling. Transbound Emerg Dis, 2024, 5586647. https://doi.org/10.1155/2024/5586647

Publication

Transboundary and emerging diseases
ISSN: 1865-1682
NlmUniqueID: 101319538
Country: Germany
Language: English
Volume: 2024
Pages: 5586647
PII: 5586647

Researcher Affiliations

Kim, KwangHyok
  • College of Wildlife and Protected Area Northeast Forestry University, Harbin, Heilongjiang Province, China.
  • Key Laboratory of Wildlife Diseases and Bio-Security Management of Heilongjiang Province, Harbin, Heilongjiang Province, China.
  • Institute of Animal Genetic Engineering Branch of Biotechnology State Academy of Sciences, Pyongyang, Democratic People's Republic of Korea.
Xu, TianGang
  • China Animal Health and Epidemiology Center, Qingdao, Shandong Province, China.
Kannan Villalan, Arivizhivendhan
  • College of Wildlife and Protected Area Northeast Forestry University, Harbin, Heilongjiang Province, China.
  • Key Laboratory of Wildlife Diseases and Bio-Security Management of Heilongjiang Province, Harbin, Heilongjiang Province, China.
Chi, TianYing
  • China Animal Health and Epidemiology Center, Qingdao, Shandong Province, China.
Yu, XiaoJing
  • China Animal Health and Epidemiology Center, Qingdao, Shandong Province, China.
Jin, MyongIl
  • Kyeungsang Sariwon University of Agriculture, Sariwon, Democratic People's Republic of Korea.
Wu, RenNa
  • HaiXi Animal Disease Control Center, Delingha, Qinghai Province, China.
Ni, GuanYing
  • HaiXi Animal Disease Control Center, Delingha, Qinghai Province, China.
Sui, ShiFeng
  • Zhaoyuan Forest Resources Monitoring and Protection Service Center, Zhaoyuan, Shandong Province, China.
Wang, ZhiLiang
  • China Animal Health and Epidemiology Center, Qingdao, Shandong Province, China.
Wang, XiaoLong
  • College of Wildlife and Protected Area Northeast Forestry University, Harbin, Heilongjiang Province, China.
  • Key Laboratory of Wildlife Diseases and Bio-Security Management of Heilongjiang Province, Harbin, Heilongjiang Province, China.

MeSH Terms

  • Animals
  • Horses
  • African Horse Sickness / epidemiology
  • African Horse Sickness / transmission
  • African Horse Sickness / virology
  • African Horse Sickness / history
  • Environment
  • Risk Factors

Conflict of Interest Statement

The authors declare that they have no conflicts of interest.

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Citations

This article has been cited 1 times.
  1. Pipitpornsirikul P, Thangthamniyom N, Laikul A, Songkasupa T, Pathomsakulwong W, Apichaimongkonkun T, Kasemsuwan S, E-Kobon T, Lekcharoensuk P. The Viremic Phase and Humoral Immune Response Against African Horse Sickness Virus That Emerged in Thailand in 2020.. Vet Sci 2025 Sep 11;12(9).
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