Effects of the Fort McMurray wildfires on the health of evacuated workers: follow-up of 2 cohorts
Bibliographic record
Abstract
Background: Wildfire engulfed Fort McMurray, Alberta on May 3, 2016, leading to a total evacuation. Access to 2 active cohorts allowed us to rapidly assess health effects in those evacuated. Methods: People working in Fort McMurray who had been recruited before the fire for 2 occupational health cohort studies completed a questionnaire (online or via telephone) 3-26 weeks after evacuation. The questionnaire asked about respiratory and mental health and experiences since the fire. Results: Of the 129 participants, 109 were in the Fort McMurray area on May 3. Thirty-seven (33.9%) of the participants who were in Fort McMurray on May 3 reported a health condition, including respiratory symptoms (n = 17) and mental ill health (n = 17), immediately after the fire. At follow-up, a mean of 102 days after the fire, 11 participants (10.1%) reported a fire-related health condition, including mental ill health (n = 8) and respiratory symptoms (n = 2). There was no difference before and after the fire in use of alcohol, cigarettes, recreational drugs or medication. One in 4 participants (32 [24.6%]) had not worked since the fire, and fewer than half (58 [44.6%]) had returned to Fort McMurray. Of the 90 participants evacuated, 15 (16.7%) had scores indicative of moderate or severe anxiety or depression on the Hospital Anxiety and Depression Scale. Those evacuated had significantly higher mean anxiety (p = 0.01) and depression (p = 0.04) scores than those not evacuated. Regression modelling showed that anxiety scores were higher for women, with longer time since the fire and with evacuation to a motel. Depression scores were higher for women and with financial loss because of lack of work. Interpretation: Although evacuation was associated with higher anxiety and depression scores, persisting ill health was not widespread at early follow-up after the fire. Although these results are encouraging, these "healthy worker" results cannot be generalized to all evacuees.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".