Sentinel surveillance contributes to tracking lyme disease spatiotemporal risk trends in southern Quebec, Canada

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creativework.keywords - en
sentinel surveillance
Lyme disease
tick-borne diseases
dc.contributor.author
Guillot, Camille
Bouchard, Catherine
Buhler, Kayla
Dumas, Ariane
Milord, François
Ripoche, Marion
Pelletier, Roxane
Leighton, Patrick A.
dc.date.accessioned
2024-03-08T19:10:22Z
dc.date.available
2024-03-08T19:10:22Z
dc.date.issued
2022-05-02
dc.description - en
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.
dc.description.abstract - en
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.
dc.identifier.doi
https://doi.org/10.3390/pathogens11050531
dc.identifier.issn
2076-0817
dc.identifier.pubmedID
35631052
dc.identifier.uri
https://open-science.canada.ca/handle/123456789/2037
dc.language.iso
en
dc.publisher
MDPI
dc.rights - en
Creative Commons Attribution 4.0 International (CC BY 4.0)
dc.rights - fr
Creative Commons Attribution 4.0 International (CC BY 4.0)
dc.rights.openaccesslevel - en
Gold
dc.rights.openaccesslevel - fr
Or
dc.rights.uri - en
https://creativecommons.org/licenses/by/4.0/
dc.rights.uri - fr
https://creativecommons.org/licenses/by/4.0/deed.fr
dc.subject - en
Health
dc.subject - fr
Santé
dc.subject.en - en
Health
dc.subject.fr - fr
Santé
dc.title - en
Sentinel surveillance contributes to tracking lyme disease spatiotemporal risk trends in southern Quebec, Canada
dc.type - en
Article
dc.type - fr
Article
local.acceptedmanuscript.articlenum
531
local.article.journalissue
5
local.article.journaltitle
Pathogens
local.article.journalvolume
11
local.pagination
1-14
local.peerreview - en
Yes
local.peerreview - fr
Oui
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