Analysis of community deaths during the catastrophic 2021 heat dome
Bibliographic record
Abstract
BACKGROUND: British Columbia, Canada, was impacted by a record-setting heat dome in early summer 2021. Most households in greater Vancouver do not have air conditioning, and there was a 440% increase in community deaths during the event. Readily available data were analyzed to inform modifications to the public health response during subsequent events in summer 2021 and to guide further research. METHODS: The 434 community deaths from 27 June through 02 July 2021 (heat dome deaths) were compared with all 1,367 community deaths that occurred in the same region from 19 June through 09 July of 2013-2020 (typical weather deaths). Conditional logistic regression was used to examine the effects of age, sex, neighborhood deprivation, and the surrounding environment. Data available from homes with and without air conditioning were also used to illustrate the indoor temperatures differences. RESULTS: A combined index of material and social deprivation was most predictive of heat dome risk, with an adjusted odds ratio of 2.88 [1.85, 4.49] for the most deprived category. Heat dome deaths also had lower greenness within 100 m than typical weather deaths. Indoor temperatures in one illustrative home without air conditioning ranged between 30°C and 40°C. CONCLUSIONS: Risk of death during the heat dome was associated with deprivation, lower neighborhood greenness, older age, and sex. High indoor temperatures likely played an important role. Public health response should focus on highly deprived neighborhoods with low air conditioning prevalence during extreme heat events. Promotion of urban greenspace must continue as the climate changes.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".