The Health of Firefighters Deployed to the Fort McMurray Fire: Lessons Learnt
Bibliographic record
Abstract
Introduction: Firefighters were working in exceptionally difficult conditions during the Fort McMurray/Horse River fire in May 2016. Methods: From mid-May, we recruited firefighters from 13 fire services as they returned from the fire. In October 2016 we extended recruitment to all Alberta-based firefighters deployed to the fire. In December 2017–May 2018 we sent a first online follow-up: this concentrated on mental health supports. The second follow-up, in October 2018–January 2019, included screening scales for respiratory ill-health and PTSD. All three contacts included visual analogue scales for chest symptoms and the Hospital Anxiety and Depression Scale. We estimated exposure to PM 2.5 , and calculated an exposure mitigation index from reports of respiratory protective equipment (RPE). Results: We recruited 1,234 firefighters and examined the relation of respiratory symptoms to estimated particulate exposure. The relation was strong immediately post fire but weakened over time. We found less chest tightness and cough in those whose RPE in the first week mitigated exposure by at least 10%. We examined the relation between particulate exposure and mental ill-health from screening questionnaires and found those with high exposure (reflecting the ferocity of the fire) had poorer mental health scores. Firefighters reporting their “worst moment during the fire” was life threatening were more anxious at second follow-up. Overall both anxiety and depression scores increased at successive contacts, more so in those with mental ill-health recorded in physician billing records before the fire. Discussion: The results from this study overall suggest on-going fire-related health effects in a substantial minority of firefighters, similar to those reported in the longitudinal follow-up of firefighters after the collapse of the World Trade Centre. Self-reports of both respiratory symptoms and mental ill-health were strongly related, soon after the fire, to estimated particulate exposures. Anxiety increased over time since the fire in those who felt their life or safety had been threatened, underlining the need for ongoing support. Our conclusions about the benefits of rapid research relate particularly to the collection of biomarkers of exposure as quickly and widely as possible, and the establishment of a nominal list of participants before they are too widely dispersed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".