Chikungunya in travellers returning to Canada: Surveillance report from CanTravNet surveillance data, 2006 to 2015
Bibliographic record
Abstract
BACKGROUND: Established in the Americas since late 2013, chikungunya is an emerging infection among travellers. OBJECTIVE: To examine demographic and travel correlates of chikungunya among Canadian travellers to establish a detailed epidemiological framework of this infection for Canadian practitioners encountering prospective and returned travellers. METHODS: Data regarding ill returned Canadian travellers presenting to a CanTravNet site between 2006 and 2015 were analyzed. RESULTS: During the study period, 22,387 ill travellers and immigrants presented to a CanTravNet site and, of these, 118 (0.5%) received a diagnosis of chikungunya. Those travelling for tourism were the most well-represented (n=49, 41.5%), followed by those travelling to visit friends and relatives (n=36, 30.5%). The Caribbean was the most likely source region, accounting for 64 (54.2%) diagnoses, followed by South Central Asia (n=18, 15.3%). Haiti was the most well-represented source country, accounting for 22 (18.6%) cases. India, a high-volume destination for Canadians and the next most well-represented source country, accounted for 15 cases (12.7%), as did Jamaica. Median trip duration of those with chikungunya was 14 days, with 51.7% (n=61) having a trip duration of ≤2 weeks and 21.2% (n=25) ≤1 week. Musculoskeletal complaints at presentation were noted in 89% (n=105), followed by fever in 54.2% (n=64). CONCLUSIONS: The present analysis provides an epidemiological framework of chikungunya for Canadian practitioners encountering prospective and returned travellers. It reflects the emergence of chikungunya in the Americas, the risk associated with short-duration travel and substantiates efforts to educate travellers about the need for mosquito avoidance.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".