SOS! Summer of Smoke: a retrospective cohort study examining the cardiorespiratory impacts of a severe and prolonged wildfire season in Canada’s high subarctic
Bibliographic record
Abstract
OBJECTIVES: To determine healthcare service utilisation for cardiorespiratory presentations and outpatient salbutamol dispensation associated with 2.5 months of severe, unabating wildfire smoke in Canada's high subarctic. DESIGN: A retrospective cohort study using hospital, clinic, pharmacy and environmental data analysed using Poisson regression. SETTING: Territorial referral hospital and clinics in Yellowknife, Northwest Territories, Canada. PARTICIPANTS: Individuals from Yellowknife and surrounding communities presenting for care between 2012 and 2015. MAIN OUTCOME MEASURES: was associated with an increase in asthma-related (incidence rate ratio (IRR) (95% CI): 1.11 (1.07, 1.14)) and pneumonia-related ER visits (IRR (95% CI): 1.06 (1.02, 1.10)), as well as an increase in chronic obstructive pulmonary disease hospitalisations (IRR (95% CI): 1.11 (1.02, 1.20). Compared with 2012 and 2013, salbutamol dispensations in 2014 increased by 48%; clinic visits for asthma, pneumonia and cough increased; ER visits for asthma doubled, with the highest rate in females, in adults aged ≥40 years and in Dene people, while pneumonia increased by 57%, with higher rates in males, in individualsaged <40 years and in Inuit people. Cardiac variables were unchanged. CONCLUSIONS: Severe wildfires in 2014 resulted in extended poor air quality associated with increases in health resource utilization; some impacts were seen disproportionately among vulnerable populations, such as children and Indigenous individuals. Public health advisories asking people to stay inside were inadequately protective, with compliance possibly impacted by the prolonged exposure. Future research should investigate use of at-home air filtration systems, clean-air shelters and public health messaging which addresses mental health and supports physical activity.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".