Sentinel Surveillance Contributes to Tracking Lyme Disease Spatiotemporal Risk Trends in Southern Quebec, Canada
Camille Guillot,
Catherine Bouchard,
Kayla Buhler,
Ariane Dumas,
François Milord,
Marion Ripoche,
Roxane Pelletier,
Patrick A. Leighton
Affiliations
Camille Guillot
Groupe de Recherche en Épidémiologie des Zoonoses et Santé Publique (GREZOSP), Departement of Pathology and Microbiology, Faculty of Veterinary Medicine, University of Montreal, Montreal, QC J2S 2M1, Canada
Catherine Bouchard
Public Health Risk Sciences Divisions, National Microbiology Laboratory, Public Health Agency of Canada, St. Hyacinthe, QC J2S 2M1, Canada
Kayla Buhler
Departement of Veterinary Microbiology, Western College of Veterinary Medicine, University of Saskatchewan, Saskatoon, SK S7N 5B4, Canada
Ariane Dumas
Groupe de Recherche en Épidémiologie des Zoonoses et Santé Publique (GREZOSP), Departement of Pathology and Microbiology, Faculty of Veterinary Medicine, University of Montreal, Montreal, QC J2S 2M1, Canada
François Milord
Faculty of Medicine and Health Sciences, University of Sherbrooke, Sherbrooke, QC J1H 5N4, Canada
Marion Ripoche
Department of Biological Risks, Institut National de Santé Publique du Québec (INSPQ), Montreal, QC H2P 1E2, Canada
Roxane Pelletier
Department of Biological Risks, Institut National de Santé Publique du Québec (INSPQ), Montreal, QC H2P 1E2, Canada
Patrick A. Leighton
Groupe de Recherche en Épidémiologie des Zoonoses et Santé Publique (GREZOSP), Departement of Pathology and Microbiology, Faculty of Veterinary Medicine, University of Montreal, Montreal, QC J2S 2M1, Canada
Lyme disease (LD) is a tick-borne disease which has been emerging in temperate areas in North America, Europe, and Asia. In Quebec, Canada, the number of human LD cases is increasing rapidly and thus surveillance of LD risk is a public health priority. In this study, we aimed to evaluate the ability of active sentinel surveillance to track spatiotemporal trends in LD risk. Using drag flannel data from 2015–2019, we calculated density of nymphal ticks (DON), an index of enzootic hazard, across the study region (southern Quebec). A Poisson regression model was used to explore the association between the enzootic hazard and LD risk (annual number of human cases) at the municipal level. Predictions from models were able to track both spatial and interannual variation in risk. Furthermore, a risk map produced by using model predictions closely matched the official risk map published by provincial public health authorities, which requires the use of complex criteria-based risk assessment. Our study shows that active sentinel surveillance in Quebec provides a sustainable system to follow spatiotemporal trends in LD risk. Such a network can support public health authorities in informing the public about LD risk within their region or municipality and this method could be extended to support Lyme disease risk assessment at the national level in Canada.