Systematic community- and hospital-based surveillance for enterovirus-D68 in three Canadian provinces, August to December 2014
Bibliographic record
Abstract
Respiratory specimens collected from outpatients with influenza-like illness in three Canadian provinces (British Columbia (BC), Alberta and Quebec) participating in a community-based sentinel surveillance network were prospectively screened for enterovirus-D68 (EV-D68) from 1 August to 31 December 2014 and compared to specimens collected from 1 October 2013 to 31 July 2014. Eighteen (1%) of 1,894 specimens were EV-D68-positive: 1/348 (0.3%) collected from October to December 2013 and 11/460 (2.4%) from October to December 2014, an eight-fold increase in detection rates (p=0.01), consistent with epidemic circulation in autumn 2014. The remaining EV-D68 detections were in September 2014 (6/37). Enhanced passive surveillance was also conducted on all inpatient and outpatient EV-D68 cases (n=211) detected at the BC provincial reference laboratory from 28 August to 31 December 2014. Incidence of hospitalisations was 3/100,000 overall and 21, 17, 4 and 1/100,000 among those<5, 5-9, 10-19 and ≥20-years-old with male-to-female ratios>1 among paediatric but not adult cases. Three cases in BC with comorbidity or co-infection died and five exhibited neurological features persisting >9 months. Active surveillance in outpatient and inpatient settings is needed from more areas and additional seasons to better understand EV-D68 epidemiology and potential at-risk groups for severe or unusual manifestations.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".