Modelling Spatiotemporal Patterns of Lyme Disease Emergence in Québec
Abstract
:1. Introduction
2. Materials and Methods
2.1. Data
2.2. Surface Trend Analysis
2.3. Cluster Analysis
3. Results
3.1. Surface Trend Analysis
3.2. Cluster Analysis
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Acknowledgments
Conflicts of Interest
References
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Case Definition | |||
---|---|---|---|
Scenarios | Date of Symptom Onset | Date of Notification | |
1 | First case for each municipality between 2006–2018 | A1 | B1 |
2 | Municipalities with at least two cases between 2013–2018 | A2 | B2 |
3 | Municipalities with at least two cases between 2006–2018 | A3 | B3 |
All Years | 2006–2012 | 2013–2018 | |
---|---|---|---|
Total cases | 727 | 25 | 702 |
Number of municipalities with at least 1 case | 138 | 20 | 136 |
Male (%) | 413 (56.8%) | 17 (68.0%) | 396 (56.4%) * |
Number of cases per age group | |||
1–9 | 77 | 2 | 75 |
10–19 | 59 | 2 | 57 |
20–29 | 49 | 1 | 48 |
30–39 | 79 | 3 | 76 |
40–49 | 81 | 4 | 77 |
50–59 | 140 | 5 | 135 |
60–69 | 171 | 6 | 165 |
70–79 | 62 | 2 | 60 |
80–89 | 9 | 0 | 9 |
Average time from symptom onset to medical consultation (days) | 59 § | 57 † | 59 ‡ |
Model A1 * | Model B1 † | |
Northern spread (km/year) § | 32 km/year | 18 km/year |
Average velocity (km/year deg) | 34 km/year 341° NNW | 21 km/year 327° NWN |
Range (km/year) | 2–568 km/year | 14.5–2,949 km/year |
SD | 67 km/year | 258 km/year |
Model A2 ** | Model B2 †† | |
Northern spread (km/year) § | 40 km/year | 46 km/year |
Average velocity (km/year deg) | 41 km/year 16° NE | 47 km/year 15° NE |
Range (km/year) | 21–107 km/year | 13–107 km/year |
SD | 22 km/year | 19 km/year |
Model A3 *** | Model B3 ††† | |
Northern spread (km/year) § | 46 km/year | 44 km/year |
Average velocity (km/year deg) | 46 km/year 357° N | 44 km/year 11° NE |
Range (km/year) | 13–82 km/year | 12–103 km/year |
SD | 16 km/year | 17 km/year |
Clusters | |||||||
---|---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | 5 | 6 | 7 | |
Radius (km) | 20.80 | 24.81 | 20.41 | 23.97 | 23.67 | 14.05 | 12.33 |
Time period | 2013–2018 | 2013–2018 | 2013–2018 | 2015–2018 | 2015–2018 | 2015–2018 | 2016–2018 |
Municipalities at-risk | 15 | 14 | 8 | 14 | 4 | 2 | 7 |
Population at-risk | 52,675 | 26,423 | 15,645 | 100,670 | 7239 | 2074 | 109,448 |
Declared cases | 282 | 75 | 40 | 88 | 6 | 5 | 48 |
Expected cases | 4.68 | 2.35 | 1.39 | 5.96 | 0.43 | 0.12 | 4.86 |
Annual cases/100,000 | 89.2 | 47.3 | 42.6 | 21.9 | 20.7 | 60.3 | 14.6 |
Relative risk | 97.80 | 35.51 | 30.39 | 16.65 | 14.10 | 40.96 | 10.49 |
p-value | <0.001 | <0.001 | <0.01 | <0.001 | 0.022 | 0.0013 | <0.01 |
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Tutt-Guérette, M.-A.; Yuan, M.; Szaroz, D.; McKinnon, B.; Kestens, Y.; Guillot, C.; Leighton, P.; Zinszer, K. Modelling Spatiotemporal Patterns of Lyme Disease Emergence in Québec. Int. J. Environ. Res. Public Health 2021, 18, 9669. https://doi.org/10.3390/ijerph18189669
Tutt-Guérette M-A, Yuan M, Szaroz D, McKinnon B, Kestens Y, Guillot C, Leighton P, Zinszer K. Modelling Spatiotemporal Patterns of Lyme Disease Emergence in Québec. International Journal of Environmental Research and Public Health. 2021; 18(18):9669. https://doi.org/10.3390/ijerph18189669
Chicago/Turabian StyleTutt-Guérette, Marc-Antoine, Mengru Yuan, Daniel Szaroz, Britt McKinnon, Yan Kestens, Camille Guillot, Patrick Leighton, and Kate Zinszer. 2021. "Modelling Spatiotemporal Patterns of Lyme Disease Emergence in Québec" International Journal of Environmental Research and Public Health 18, no. 18: 9669. https://doi.org/10.3390/ijerph18189669