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Home / Equine Research Bank / Can J Vet Res / Stochastic modeling of the horse population and vaccination ...
Canadian journal of veterinary research = Revue canadienne de recherche veterinaire2025; 89(2); 54-63;

Stochastic modeling of the horse population and vaccination data indicates low annual vaccination coverage for West Nile virus in Canada (2016-2020).

Abstract: Vaccination is the most efficient tool for preventing West Nile virus (WNV) disease in horses. The objectives of this retrospective study were to: i) estimate the provincial and national horse population in Canada; ii) estimate the annual vaccination coverage for WNV in each province; and iii) compare estimates of provincial annual vaccination coverage. Horse population data (2006-2023) and the number of vaccine doses sold in Canada (2016-2020) were obtained by province. Based on these data and expert consultations, the annual number of vaccine doses administered, and provincial horse populations were modeled at the provincial level using Program Evaluation and Review Technique (PERT) distributions, whereas the probability of primary vaccination in vaccinated horses was modeled with a uniform distribution. The annual number of horses vaccinated was estimated using a binomial distribution. Monte Carlo simulations were used to estimate provincial annual vaccination coverage with 95% credible intervals (CI). National horse population and vaccination coverage were estimated by summing the provincial estimates. The national horse population in Canada (2016-2020) was estimated at 795 420 horses, with a vaccination coverage of 16% (95% CI: 13 to 20%). The vaccination coverage estimates for WNV ranged from 10% (95% CI: 6 to 20%) in the Atlantic provinces to 35% (95% CI: 22 to 53%) in Manitoba. The coverage was significantly higher (P ≤ 0.01) in Manitoba than in the Atlantic provinces, Saskatchewan, Alberta, and British Columbia. The study revealed low annual WNV vaccination coverage across Canada, emphasizing the need to promote vaccination and collect more comprehensive data on horse population, as uncertainties in these data drive the uncertainty in vaccination coverage based on model sensitivity analysis. La vaccination est l’outil le plus efficace pour prévenir la maladie causée par le virus du Nil occidental (VNO) chez les chevaux. Une étude rétrospective a été menée au Canada pour i) estimer les populations provinciales et nationales de chevaux, ii) estimer la couverture vaccinale provinciale annuelle pour le VNO et iii) comparer les couvertures vaccinales annuelles entre les provinces. Les données sur la population équine au Canada (2006–2023) et le nombre de doses de vaccin vendues (2016–2020) ont été collectés par province. Avec ces données et l’avis d’experts, le nombre annuel de doses de vaccin administrées et les populations provinciales de chevaux ont été modélisées avec des distributions PERT, alors que la probabilité de primovaccination parmi les chevaux vaccinés a été modélisée avec une distribution uniforme. Le nombre de chevaux vaccinés annuellement a été estimé avec une distribution binomiale. Des simulations de Monte Carlo ont permis d’estimer la couverture vaccinale annuelle avec des intervalles de crédibilité (IC 95 %). La population nationale de chevaux (2016–2020) a été estimée à 795 420 chevaux avec une couverture vaccinale de 16 % (IC 95 % : 13 %–20 %). Une couverture vaccinale allant de 10 % (IC 95 % : 6 %–20 %) dans les provinces de l’Atlantique à 35 % (95 % IC : 22 %–53 %) au Manitoba a été estimée, avec une couverture significativement plus élevée (P ≤ 0,01) au Manitoba qu’en Colombie-Britannique, Alberta, Saskatchewan et dans les provinces d’Atlantique. Les résultats de l’étude indiquent une faible couverture vaccinale annuelle contre le VNO à travers le Canada, illustrant la nécessité de promouvoir la vaccination et d’obtenir des données plus complètes sur la population équine. En effet, l’incertitude des données de population est celle qui influence le plus l’incertitude des résultats de couverture vaccinale selon l’analyse de sensibilité du modèle.(Traduit par les auteurs).
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Publication Date: 2025-04-02 PubMed ID: 40170915PubMed Central: PMC11924128
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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.

This research study reveals that the annual vaccination coverage for West Nile Virus (WNV) in the Canadian horse population between 2016 and 2020 was low. It shows that coverage varied between provinces with Manitoba achieving the highest rate. The study underscores the need for more comprehensive horse population data and promotes vaccination against WNV to protect horses better.

Study Objectives and Methodology

  • The study aimed to estimate the Canadian national and provincial horse populations, calculate yearly WNV vaccination protection levels in each province, and contrast these estimates.
  • Data were gathered on horse populations (2006-2023) and the number of vaccine doses sold (2016-2020) in each province.
  • Following expert consultations, the annual number of vaccine doses given and provincial horse populations were predicted at a provincial level using Program Evaluation and Review Technique (PERT) distributions.
  • The likelihood of primary vaccination in vaccinated horses was modeled with a uniform distribution.
  • The annual number of horses vaccinated was estimated using a binomial distribution.
  • Monte Carlo simulations were used to estimate yearly provincial vaccination coverage with 95% credible intervals (CI).
  • Estimates for the national horse population and vaccination coverage were arrived at by adding up the provincial estimates.

Findings

  • The national horse population in Canada (2016-2020) was estimated at around 795,420 horses, with a vaccination coverage of 16% (CI: 13 to 20%).
  • Vaccination protection rates for WNV varied widely across the provinces, from 10% (CI: 6 to 20%) in the Atlantic provinces to 35% (CI: 22 to 53%) in Manitoba. This variation is important as it shows disparities in protection against WNV among horses in different provinces.
  • Manitoba had substantially higher coverage ( ≤ 0.01) than the Atlantic provinces, Saskatchewan, Alberta, and British Columbia, indicating regional variations in vaccination coverage.

Implications

  • This study showed low annual vaccination coverage against WNV across Canada, indicating that many horses might not be adequately protected against this virus.
  • Given these results, there is a need to encourage vaccination and gather more comprehensive data on the horse population in Canada. The lack of precise data on the horse population contributes to the uncertainty in vaccination coverage, thereby affecting the model’s sensitivity analysis. Accurate information is critical for assessing the risk of disease and planning effective vaccination strategies.

Cite This Article

APA
Levasseur A, Paré J, Aubry P, Iwasawa S, Leung D, Arsenault J. (2025). Stochastic modeling of the horse population and vaccination data indicates low annual vaccination coverage for West Nile virus in Canada (2016-2020). Can J Vet Res, 89(2), 54-63.

Publication

Canadian journal of veterinary research = Revue canadienne de recherche veterinaire
ISSN: 1928-9022
NlmUniqueID: 8607793
Country: Canada
Language: English
Volume: 89
Issue: 2
Pages: 54-63

Researcher Affiliations

Levasseur, Antoine
  • Groupe de recherche en épidémiologie des zoonoses et santé publique (GREZOSP) and Département de pathologie et microbiologie vétérinaire, Faculté de médecine vétérinaire, Université de Montréal, 3200 rue Sicotte, Saint-Hyacinthe, Québec J2S 2M2 (Levasseur, Paré, Arsenault); Animal Health Science Directorate, Canadian Food Inspection Agency, 3200 rue Sicotte, Saint-Hyacinthe, Québec J2S 2M2 (Paré); Animal Health Science Directorate, Canadian Food Inspection Agency, 1400 Merivale Road, Ottawa, Ontario K1A 0Y9 (Aubry); Canadian Animal Health Surveillance System, Animal Health Canada, P.O. Box 3013 RPO, Elora, Ontario N0B 1S0 (Iwasawa, Leung).
Paré, Julie
  • Groupe de recherche en épidémiologie des zoonoses et santé publique (GREZOSP) and Département de pathologie et microbiologie vétérinaire, Faculté de médecine vétérinaire, Université de Montréal, 3200 rue Sicotte, Saint-Hyacinthe, Québec J2S 2M2 (Levasseur, Paré, Arsenault); Animal Health Science Directorate, Canadian Food Inspection Agency, 3200 rue Sicotte, Saint-Hyacinthe, Québec J2S 2M2 (Paré); Animal Health Science Directorate, Canadian Food Inspection Agency, 1400 Merivale Road, Ottawa, Ontario K1A 0Y9 (Aubry); Canadian Animal Health Surveillance System, Animal Health Canada, P.O. Box 3013 RPO, Elora, Ontario N0B 1S0 (Iwasawa, Leung).
Aubry, Pascale
  • Groupe de recherche en épidémiologie des zoonoses et santé publique (GREZOSP) and Département de pathologie et microbiologie vétérinaire, Faculté de médecine vétérinaire, Université de Montréal, 3200 rue Sicotte, Saint-Hyacinthe, Québec J2S 2M2 (Levasseur, Paré, Arsenault); Animal Health Science Directorate, Canadian Food Inspection Agency, 3200 rue Sicotte, Saint-Hyacinthe, Québec J2S 2M2 (Paré); Animal Health Science Directorate, Canadian Food Inspection Agency, 1400 Merivale Road, Ottawa, Ontario K1A 0Y9 (Aubry); Canadian Animal Health Surveillance System, Animal Health Canada, P.O. Box 3013 RPO, Elora, Ontario N0B 1S0 (Iwasawa, Leung).
Iwasawa, Stefan
  • Groupe de recherche en épidémiologie des zoonoses et santé publique (GREZOSP) and Département de pathologie et microbiologie vétérinaire, Faculté de médecine vétérinaire, Université de Montréal, 3200 rue Sicotte, Saint-Hyacinthe, Québec J2S 2M2 (Levasseur, Paré, Arsenault); Animal Health Science Directorate, Canadian Food Inspection Agency, 3200 rue Sicotte, Saint-Hyacinthe, Québec J2S 2M2 (Paré); Animal Health Science Directorate, Canadian Food Inspection Agency, 1400 Merivale Road, Ottawa, Ontario K1A 0Y9 (Aubry); Canadian Animal Health Surveillance System, Animal Health Canada, P.O. Box 3013 RPO, Elora, Ontario N0B 1S0 (Iwasawa, Leung).
Leung, Doris
  • Groupe de recherche en épidémiologie des zoonoses et santé publique (GREZOSP) and Département de pathologie et microbiologie vétérinaire, Faculté de médecine vétérinaire, Université de Montréal, 3200 rue Sicotte, Saint-Hyacinthe, Québec J2S 2M2 (Levasseur, Paré, Arsenault); Animal Health Science Directorate, Canadian Food Inspection Agency, 3200 rue Sicotte, Saint-Hyacinthe, Québec J2S 2M2 (Paré); Animal Health Science Directorate, Canadian Food Inspection Agency, 1400 Merivale Road, Ottawa, Ontario K1A 0Y9 (Aubry); Canadian Animal Health Surveillance System, Animal Health Canada, P.O. Box 3013 RPO, Elora, Ontario N0B 1S0 (Iwasawa, Leung).
Arsenault, Julie
  • Groupe de recherche en épidémiologie des zoonoses et santé publique (GREZOSP) and Département de pathologie et microbiologie vétérinaire, Faculté de médecine vétérinaire, Université de Montréal, 3200 rue Sicotte, Saint-Hyacinthe, Québec J2S 2M2 (Levasseur, Paré, Arsenault); Animal Health Science Directorate, Canadian Food Inspection Agency, 3200 rue Sicotte, Saint-Hyacinthe, Québec J2S 2M2 (Paré); Animal Health Science Directorate, Canadian Food Inspection Agency, 1400 Merivale Road, Ottawa, Ontario K1A 0Y9 (Aubry); Canadian Animal Health Surveillance System, Animal Health Canada, P.O. Box 3013 RPO, Elora, Ontario N0B 1S0 (Iwasawa, Leung).

MeSH Terms

  • Animals
  • Horses
  • Horse Diseases / prevention & control
  • Horse Diseases / epidemiology
  • Horse Diseases / virology
  • West Nile Fever / veterinary
  • West Nile Fever / prevention & control
  • West Nile Fever / epidemiology
  • Canada / epidemiology
  • Retrospective Studies
  • Vaccination / veterinary
  • Vaccination / statistics & numerical data
  • West Nile Virus Vaccines / administration & dosage
  • West Nile Virus Vaccines / immunology
  • West Nile virus / immunology
  • Vaccination Coverage / statistics & numerical data
  • Stochastic Processes

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