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Transboundary and emerging diseases2014; 63(5); 564-573; doi: 10.1111/tbed.12302

Identification of Suitable Areas for African Horse Sickness Virus Infections in Spanish Equine Populations.

Abstract: African horse sickness (AHS) is one of the most important vector-borne viral infectious diseases of equines, transmitted mainly by Culicoides spp. The re-emergence of Culicoides-borne diseases in Europe, such as the recent bluetongue (BT) or Schmallenberg outbreaks, has raised concern about the potential re-introduction and further spread of AHS virus (AHSV) in Europe. Spain has one of the largest European equine populations. In addition, its geographical, environmental and entomological conditions favour AHSV infections, as shown by the historical outbreaks in the 1990s. The establishment of risk-based surveillance strategies would allow the early detection and rapid control of any potential AHSV outbreak. This study aimed to identify the areas and time periods that are suitable or at high risk for AHS occurrence in Spain using a GIS-based multicriteria decision framework. Specifically risk maps for AHS occurrence were produced using a weighted linear combination of the main risk factors of disease, namely extrinsic incubation period, equine density and distribution of competent Culicoides populations. Model results revealed that the south-western and north-central areas of Spain and the Balearic Islands are the areas at the highest risk for AHSV infections, particularly in late summer months. Conversely, Galicia, Castile and Leon and La Rioja can be considered as low-risk regions. This result was validated with historical AHS and BT outbreaks in Spain, and with the Culicoides vector distribution area. The model results, together with current Spanish equine production features, should provide the foundations to design risk-based and more cost-effective surveillance strategies for the early detection and rapid control potential of AHS outbreaks in Spain.
Publication Date: 2014-12-05 PubMed ID: 25476549DOI: 10.1111/tbed.12302Google Scholar: Lookup
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  • Journal Article

Summary

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This research article focuses on identifying the regions in Spain most susceptible to African Horse Sickness Virus (AHS) targeting equine populations. Utilizing a Geographic Information System (GIS)-based multicriteria decision framework, the study aimed to map areas and periods of high risk, in order to implement more effective surveillance and control strategies.

Background

  • African Horse Sickness (AHS) is a major threat to horse populations and is primarily spread by the Culicoides spp species of biting insects.
  • In recent years, re-emergence of diseases spread by Culicoides in Europe, including the bluetongue and Schmallenberg outbreaks, has led to concerns about a potential future spread of AHS in Europe, particularly in Spain which has a large equine population.
  • Previous AHS outbreaks in Spain during the 1990s, along with the country’s geographical and environmental conditions, suggest a high potential for AHSV infections.

Research Aim and Methodology

  • The aim of this study was to establish risk-based surveillance strategies for early detection and control of AHS outbreaks in Spain.
  • To do this, the researchers used a GIS-based multicriteria decision framework to identify areas and time periods at high risk for AHS.
  • The main risk factors for AHS they considered were the extrinsic incubation period (the time taken for the vector to become infectious after acquiring the virus), horse density, and distribution of competent Culicoides populations.

Results

  • The results showed that the south-western and north-central areas of Spain, along with the Balearic Islands, are at highest risk for AHSV infections, especially during the late summer months.
  • On the other hand, regions like Galicia, Castile and Leon, and La Rioja are considered as low-risk areas.
  • The study’s results were validated through previous AHS and bluetongue outbreaks in Spain and the distribution area of the Culicoides vector.

Implications

  • The findings of this study, combined with current Spanish equine production data, will contribute to designing more cost-effective surveillance strategies for early AHS detection and control.
  • The risk-based approach can inform targeted surveillance efforts, prioritizing regions of higher risk and thus improving the efficiency and effectiveness of outbreak responses.

Cite This Article

APA
Sánchez-Matamoros A, Sánchez-Vizcaíno JM, Rodríguez-Prieto V, Iglesias E, Martínez-López B. (2014). Identification of Suitable Areas for African Horse Sickness Virus Infections in Spanish Equine Populations. Transbound Emerg Dis, 63(5), 564-573. https://doi.org/10.1111/tbed.12302

Publication

ISSN: 1865-1682
NlmUniqueID: 101319538
Country: Germany
Language: English
Volume: 63
Issue: 5
Pages: 564-573

Researcher Affiliations

Sánchez-Matamoros, A
  • VISAVET Centre and Animal Health Department, Complutense University of Madrid, Madrid, Spain.
  • CEI Campus Moncloa, UCM-UPM, Madrid, Spain.
Sánchez-Vizcaíno, J M
  • VISAVET Centre and Animal Health Department, Complutense University of Madrid, Madrid, Spain.
Rodríguez-Prieto, V
  • VISAVET Centre and Animal Health Department, Complutense University of Madrid, Madrid, Spain.
Iglesias, E
  • Department of Agricultural Economics, E.T.S Agronomics Engineering, Technical University of Madrid, Madrid, Spain.
Martínez-López, B
  • VISAVET Centre and Animal Health Department, Complutense University of Madrid, Madrid, Spain.
  • Department of Medicine and Epidemiology, Center for Animal Disease Modeling and Surveillance (CADMS), University of California, Davis, CA, USA.

MeSH Terms

  • African Horse Sickness / epidemiology
  • African Horse Sickness / prevention & control
  • African Horse Sickness Virus
  • Animals
  • Ceratopogonidae / virology
  • Disease Outbreaks / veterinary
  • Horses / virology
  • Insect Vectors
  • Seasons
  • Sheep
  • Spain / epidemiology

Citations

This article has been cited 5 times.
  1. Kim K, Xu T, Kannan Villalan A, Chi T, Yu X, Jin M, Wu R, Ni G, Sui S, Wang Z, Wang X. Environmental and Historical Determinants of African Horse Sickness: Insights from Predictive Modeling. Transbound Emerg Dis 2024;2024:5586647.
    doi: 10.1155/2024/5586647pubmed: 40303017google scholar: lookup
  2. Grimaud Y, Tran A, Benkimoun S, Boucher F, Esnault O, Cêtre-Sossah C, Cardinale E, Garros C, Guis H. Spatio-temporal modelling of Culicoides Latreille (Diptera: Ceratopogonidae) populations on Reunion Island (Indian Ocean). Parasit Vectors 2021 May 27;14(1):288.
    doi: 10.1186/s13071-021-04780-9pubmed: 34044880google scholar: lookup
  3. Leta S, Fetene E, Mulatu T, Amenu K, Jaleta MB, Beyene TJ, Negussie H, Revie CW. Modeling the global distribution of Culicoides imicola: an Ensemble approach. Sci Rep 2019 Oct 2;9(1):14187.
    doi: 10.1038/s41598-019-50765-1pubmed: 31578399google scholar: lookup
  4. Leta S, Fetene E, Mulatu T, Amenu K, Jaleta MB, Beyene TJ, Negussie H, Kriticos D, Revie CW. Updating the global occurrence of Culicoides imicola, a vector for emerging viral diseases. Sci Data 2019 Sep 30;6(1):185.
    doi: 10.1038/s41597-019-0197-0pubmed: 31570721google scholar: lookup
  5. Pfeiffer DU, Stevens KB. Spatial and temporal epidemiological analysis in the Big Data era. Prev Vet Med 2015 Nov 1;122(1-2):213-20.