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Published on: June 9, 2011
Distribution of West Nile virus cases in horses reveals different spatiotemporal patterns in eastern and western
Antoine Levasseur1, Julie Arsenault1, Julie Paré1,2
11Epidemiology of Zoonoses and Public Health Research Unit (Groupe de Recherche en Épidémiologie des Zoonoses et Santé Publique) and Department of Pathology and Microbiology, Faculty of Veterinary Medicine, Université de Montréal, St-Hyacinthe, QC, Canada.
Objective:
West Nile virus (WNV) became notifiable in horses in 2003 in Canada and has been reported every year since. The objective of this study was to describe the spatiotemporal distribution of WNV in horses between 2003 and 2020 in Canada.
Animals:
The 848 symptomatic and laboratory-confirmed WNV cases in horses reported to the Canadian Food Inspection Agency between 2003 and 2020.
Methods:
Canada was divided into eastern and western regions for analysis. For each case, location and date of notification were captured. Triennial maps were made to describe the spatiotemporal distribution and expansion of reported cases. The association between year and latitude of cases was investigated with simple linear regressions, and space-time clusters were detected with a permutation scan test.
Results:
Most of the western region showed an extended distribution of WNV cases from 2003 to 2005 and a high recurrence of cases at the census division level. In the eastern region, the expansion of cases was gradual, with new infected census divisions mostly contiguous to previous ones. There was no association between year and latitude of cases. Six spatiotemporal clusters were detected.
Clinical Relevance:
This study confirmed the endemicity of WNV in parts of both regions with local peaks in risk varying in time. Prevention and control efforts should focus on previously infected areas based on the spatiotemporal regional distribution patterns. Incursions of WNV to new areas should also be anticipated. These findings could also contribute to enhancing monitoring and prevention of WNV infections in an integrated surveillance system.

