Overdose deaths and the <scp>COVID</scp>‐19 pandemic in British Columbia, Canada
Bibliographic record
Abstract
INTRODUCTION: British Columbia (BC) declared an overdose public health emergency in 2016. Since then, BC has consistently reported the highest overdose death rates of any province in Canada. In the context of the COVID-19 pandemic, overdose deaths in BC reached a record high in 2020. This analysis reports on changes in the profile of people who have died of overdose since BC's declaration of COVID-19 as a public health emergency on 17 March 2020. METHODS: Using BC Coroners Service data, Chi-square tests and multivariable logistic regression were conducted to compare demographic, geographic and post-mortem toxicology data between people who died of overdose before (17 March-31 December 2019) and after (17 March-31 December 2020) BC's declaration of COVID-19 as a public health emergency. RESULTS: Overdose deaths observed since 17 March 2020 (n = 1516) more than doubled those observed in the same period in 2019 (n = 744). In the adjusted logistic regression model, odds of death in the post compared to pre-COVID-19 period was significantly higher among males compared to females, among all older age groups compared to people aged 30-39, and was lower in public buildings compared to private residences. DISCUSSION AND CONCLUSIONS: Alongside a significant increase in overdose deaths since BC's declaration of COVID-19 as a public health emergency, the demographic profile of people who have died of overdose has changed. Ongoing overdose prevention efforts in BC must seek to reach people who remain most isolated, including older adults, who during dual public health emergencies are facing compounded risk of preventable mortality.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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".