Opioid-related deaths between 2019 and 2021 across 9 Canadian provinces and territories
Bibliographic record
Abstract
<h3>Background:</h3> The drug toxicity crisis continues to accelerate across Canada, with rapid increases in opioid-related harms following the onset of the COVID-19 pandemic. We sought to describe trends in the burden of opioid-related deaths across Canada throughout the pandemic, comparing these trends by province or territory, age, and sex. <h3>Methods:</h3> We conducted a repeated cross-sectional analysis of accidental opioid-related deaths between Jan. 1, 2019, and Dec. 31, 2021, across 9 Canadian provinces and territories using aggregated national data. Our primary measure was the burden of premature opioid-related death, measured by potential years of life lost. Our secondary measure was the proportion of all deaths attributable to opioids; we used the Cochrane–Armitage test for trend to compare proportions. <h3>Results:</h3> Between 2019 and 2021, the annual number of opioid-related deaths increased from 3007 to 6222 and years of life lost increased from 126 115 to 256 336 (from 3.5 to 7.0 yr of life lost per 1000 population). In 2021, the highest number of years of life lost was among males (181 525 yr) and people aged 30–39 years (87 045 yr). In 2019, we found that 1.7% of all deaths among those younger than 85 years were related to opioids, rising to 3.2% in 2021. Significant increases in the proportion of deaths related to opioids were observed across all age groups (<i>p</i> < 0.001), representing 29.3% and 29.0% of deaths among people aged 20–29 and 30–39 years in 2021, respectively. <h3>Interpretation:</h3> Across Canada, the burden of premature opioid-related deaths doubled between 2019 and 2021, representing more than one-quarter of deaths among younger adults. The disproportionate loss of life in this demographic group highlights the critical need for targeted prevention efforts.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 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".