Surveillance for Lyme disease in Canada, 2009 to 2012
Bibliographic record
Abstract
OBJECTIVE: To summarize seven years of surveillance data for Lyme disease cases reported in Canada from 2009 to 2015. METHODS: We describe the incidence over time, seasonal and geographic distribution, demographic and clinical characteristics of reported Lyme disease cases. Logistic regression was used to explore differences between age groups, sex and year to better understand potential demographic risk factors for the occurrence of Lyme disease. RESULTS: The number of reported Lyme disease cases increased more than six-fold, from 144 in 2009 to 917 in 2015, mainly due to an increase in infections acquired in Canada. Most locally acquired cases were reported between May and November. An increase in incidence of Lyme disease was observed in provinces from Manitoba eastwards. This is consistent with our knowledge of range expansion of the tick vectors in this region. In the western provinces the incidence has remained low and stable. All cases reported by Alberta, Saskatchewan and Newfoundland and Labrador were acquired outside of the province, either elsewhere in Canada or abroad. There was a bimodal distribution for Lyme disease by age with peaks at 5-9 and 45-74 years of age. The most common presenting symptom was a single erythema migrans rash (74.2%) and arthritis (35.7%). Variations in the frequency of reported clinical manifestations were observed among age groups and years of study. CONCLUSION: Lyme disease incidence continues to increase in Canada as does the geographic range of ticks that carry the Lyme disease bacteria. Ongoing surveillance, preventive strategies as well as early disease recognition and treatment will continue to minimize the impact of Lyme disease in Canada.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".