Self-reported tick exposure as an indicator of Lyme disease risk in an endemic region of Quebec, Canada. Bowser, N., Bouchard, C., Sautié Castellanos, M., Baron, G., Carabin, H., Chuard, P., Leighton, P., Milord, F., Richard, L., Savage, J., Tardy, O., & Aenishaenslin, C. Ticks and Tick-borne Diseases, 15(1):102271, January, 2024.
Self-reported tick exposure as an indicator of Lyme disease risk in an endemic region of Quebec, Canada [link]Paper  doi  abstract   bibtex   
Background Lyme disease (LD) and other tick-borne diseases are emerging across Canada. Spatial and temporal LD risk is typically estimated using acarological surveillance and reported human cases, the former not considering human behavior leading to tick exposure and the latter occurring after infection. Objectives The primary objective was to explore, at the census subdivision level (CSD), the associations of self-reported tick exposure, alternative risk indicators (predicted tick density, eTick submissions, public health risk level), and ecological variables (Ixodes scapularis habitat suitability index and cumulative degree days \textgreater 0 °C) with incidence proportion of LD. A secondary objective was to explore which of these predictor variables were associated with self-reported tick exposure at the CSD level. Methods Self-reported tick exposure was measured in a cross-sectional populational health survey conducted in 2018, among 10,790 respondents living in 116 CSDs of the Estrie region, Quebec, Canada. The number of reported LD cases per CSD in 2018 was obtained from the public health department. Generalized linear mixed-effets models accounting for spatial autocorrelation were built to fulfill the objectives. Results Self-reported tick exposure ranged from 0.0 % to 61.5 % (median 8.9 %) and reported LD incidence rates ranged from 0 to 324 cases per 100,000 person-years, per CSD. A positive association was found between self-reported tick exposure and LD incidence proportion (ß = 0.08, CI = 0.04,0.11, p \textless 0.0001). The best-fit model included public health risk level (AIC: 144.2), followed by predicted tick density, ecological variables, self-reported tick exposure and eTick submissions (AIC: 158.4, 158.4, 160.4 and 170.1 respectively). Predicted tick density was the only significant predictor of self-reported tick exposure (ß = 0.83, CI = 0.16,1.50, p = 0.02). Discussion This proof-of-concept study explores self-reported tick exposure as a potential indicator of LD risk using populational survey data. This approach may offer a low-cost and simple tool for evaluating LD risk and deserves further evaluation.
@article{bowser_self-reported_2024,
	title = {Self-reported tick exposure as an indicator of {Lyme} disease risk in an endemic region of {Quebec}, {Canada}},
	volume = {15},
	issn = {1877-959X},
	url = {https://www.sciencedirect.com/science/article/pii/S1877959X23001528},
	doi = {10.1016/j.ttbdis.2023.102271},
	abstract = {Background
Lyme disease (LD) and other tick-borne diseases are emerging across Canada. Spatial and temporal LD risk is typically estimated using acarological surveillance and reported human cases, the former not considering human behavior leading to tick exposure and the latter occurring after infection.
Objectives
The primary objective was to explore, at the census subdivision level (CSD), the associations of self-reported tick exposure, alternative risk indicators (predicted tick density, eTick submissions, public health risk level), and ecological variables (Ixodes scapularis habitat suitability index and cumulative degree days {\textgreater} 0 °C) with incidence proportion of LD. A secondary objective was to explore which of these predictor variables were associated with self-reported tick exposure at the CSD level.
Methods
Self-reported tick exposure was measured in a cross-sectional populational health survey conducted in 2018, among 10,790 respondents living in 116 CSDs of the Estrie region, Quebec, Canada. The number of reported LD cases per CSD in 2018 was obtained from the public health department. Generalized linear mixed-effets models accounting for spatial autocorrelation were built to fulfill the objectives.
Results
Self-reported tick exposure ranged from 0.0 \% to 61.5 \% (median 8.9 \%) and reported LD incidence rates ranged from 0 to 324 cases per 100,000 person-years, per CSD. A positive association was found between self-reported tick exposure and LD incidence proportion (ß = 0.08, CI = 0.04,0.11, p {\textless} 0.0001). The best-fit model included public health risk level (AIC: 144.2), followed by predicted tick density, ecological variables, self-reported tick exposure and eTick submissions (AIC: 158.4, 158.4, 160.4 and 170.1 respectively). Predicted tick density was the only significant predictor of self-reported tick exposure (ß = 0.83, CI = 0.16,1.50, p = 0.02).
Discussion
This proof-of-concept study explores self-reported tick exposure as a potential indicator of LD risk using populational survey data. This approach may offer a low-cost and simple tool for evaluating LD risk and deserves further evaluation.},
	number = {1},
	urldate = {2024-01-10},
	journal = {Ticks and Tick-borne Diseases},
	author = {Bowser, Natasha and Bouchard, Catherine and Sautié Castellanos, Miguel and Baron, Geneviève and Carabin, Hélène and Chuard, Pierre and Leighton, Patrick and Milord, François and Richard, Lucie and Savage, Jade and Tardy, Olivia and Aenishaenslin, Cécile},
	month = jan,
	year = {2024},
	keywords = {NALCMS},
	pages = {102271},
}
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