Predictive risk mapping of West Nile virus (WNV) infection in Saskatchewan horses.
Abstract: The objective of this study was to develop a model using equine data from geographically limited surveillance locations to predict risk categories for West Nile virus (WNV) infection in horses in all geographic locations across the province of Saskatchewan. The province was divided geographically into low-, medium-, or high-risk categories for WNV, based on available serology information from 923 horses obtained through 4 studies of WNV infection in horse populations in Saskatchewan. Discriminant analysis was used to build models using the observed risk of WNV in horses and geographic division-specific environmental data as well as to predict the risk category for all areas, including those beyond the surveillance zones. High-risk areas were indicated by relatively lower rainfall, higher temperatures, and a lower percentage of area covered in trees, water, and wetland. These conditions were most often identified in the southwest corner of the province. Environmental conditions can be used to identify those areas that are at highest risk for WNV. Public health managers could use prediction maps, which are based on animal or human information and developed from annual early season meteorological information, to guide ongoing decisions about when and where to focus intervention strategies for WNV. Cette étude avait comme objectif de développer un modèle utilisant les données provenant de chevaux de localisations géographiques limitées sous surveillance afin de prédire les catégories de risque pour l’infection par le virus du Nil occidental (WNV) chez les chevaux de toutes les localisations géographiques de la province de la Saskatchewan. La province était divisée géographiquement en trois catégories de risque pour le WNV (faible, moyen ou élevé), selon les informations sérologiques provenant de 923 chevaux ayant faits l’objet de 4 études portant sur l’infection par le WNV en Saskatchewan. Une analyse discriminante a été employée pour construire des modèles utilisant le risque observé de WVN chez les chevaux et les données environnementales spécifiques aux divisions géographiques ainsi que de prédire la catégorie de risque pour toutes les régions, incluant celles au-delà des zones de surveillance. Les régions à risque élevé étaient indiquées par des précipitations relativement faibles, des températures plus élevées et un pourcentage plus faible de superficie couverte par des arbres, de l’eau et des marais. Ces conditions étaient le plus souvent identifiées dans la portion sud-ouest de la province. Les conditions environnementales peuvent être utilisées pour identifier les régions qui sont plus à risque pour le WNV. Les gestionnaires de la santé publique pourraient utiliser les cartes de précipitation, qui sont basées sur des informations animales ou humaines et développées à partir d’informations météorologiques annuelles obtenues tôt en saison, pour aider dans la prise de décision continue sur le moment et l’endroit des stratégies d’intervention contre le WNV. (Traduit par Docteur Serge Messier)
Publication Date: 2012-01-03 PubMed ID: 22210991PubMed Central: PMC3122974
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- Journal Article
- Research Support
- Non-U.S. Gov't
- Climate
- Disease control
- Disease Prevalence
- Disease Surveillance
- Environmental Stressors
- Epidemiology
- Equine Health
- Geographical Differences
- Horses
- Infectious Disease
- Mosquito-borne Diseases
- Predictive Model
- Public Health
- Risk Factors
- Serology
- Vector-borne disease
- Veterinary Medicine
- Veterinary Research
- West Nile Virus
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.
The research study aimed to create a predictive model based on equine data from selected surveillance points to categorize the risk of West Nile virus (WNV) infection in horses throughout Saskatchewan. The model leverages serology data from 923 horses, combined with designated geographic division-specific environmental data, to predict the risk associated with WNV in areas beyond the coverage of surveillance zones.
Methods and Analysis
- For the purpose of risk classification for WNV, the province of Saskatchewan was categorized geographically into low, medium, or high-risk areas. This categorization was based on available serology information collected from 923 horses from four studies focusing on WNV infection in horse populations in Saskatchewan.
- An analytical technique known as Discriminant Analysis was utilized to construct models. The models use the observed risk of WNV infection in horses and environmental data specific to the different geographic areas.
- The objective was to predict potential risk for all terrains in the province, including those locations that were beyond the purview of the surveillance zones.
Findings
- The study revealed that areas classified as high risk for WNV were characteristically associated with relatively lower rainfall, higher temperatures, and a lesser percentage of the land covered by trees, water bodies and wetlands.
- Such environmental conditions were most frequently identified in the southwestern region of Saskatchewan province.
Conclusions and Applications
- The study illustrates that environmental conditions can serve as a reliable identification tool for those regions which are at greater risk for WNV.
- The researchers suggest that public health administrators could use these predictive maps, which make use of animal or human data and are developed from annual early-season weather-related information, to make informed decisions about when and where to concentrate intervention strategies to counter the West Nile virus.
Cite This Article
APA
Epp TY, Waldner C, Berke O.
(2012).
Predictive risk mapping of West Nile virus (WNV) infection in Saskatchewan horses.
Can J Vet Res, 75(3), 161-170.
Publication
Researcher Affiliations
- Department of Large Animal Clinical Sciences, Western College of Veterinary Medicine, University of Saskatchewan, 52 Campus Drive, Saskatoon, Saskatchewan. tasha.epp@usask.ca
MeSH Terms
- Animals
- Antibodies, Viral / blood
- Discriminant Analysis
- Enzyme-Linked Immunosorbent Assay / veterinary
- Geography
- Horse Diseases / blood
- Horse Diseases / epidemiology
- Horse Diseases / virology
- Horses
- Maps as Topic
- Models, Biological
- Population Surveillance
- Risk Assessment
- Saskatchewan / epidemiology
- Seasons
- Seroepidemiologic Studies
- Weather
- West Nile Fever / blood
- West Nile Fever / epidemiology
- West Nile Fever / veterinary
- West Nile virus / immunology
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Citations
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