Circumstances surrounding opioid toxicity deaths within shelters in Ontario, Canada, before and during the COVID-19 pandemic: a population-based descriptive cross-sectional study
Bibliographic record
Abstract
Introduction: Evidence suggests growing opioid-related toxicity deaths within shelters that has been exacerbated by the COVID-19 pandemic. We sought to characterise opioid-related toxicity deaths within Ontario shelters before and during the pandemic. Methods: A descriptive cross-sectional study of people who died of an accidental opioid toxicity, where the location of the incident (ie, toxicity) was within a shelter in Ontario, Canada, was conducted. The primary analysis was restricted to conventional shelter spaces as classified by the coroner (ie, excluding temporary COVID-19 emergency shelters in hotels). Characteristics, circumstances surrounding death and patterns of healthcare use preceding death in the pre-pandemic period (1 January 2018-16 March 2020) and the COVID-19 pandemic period (17 March 2020-31 May 2022) were summarised. Results: Overall, opioid-related toxicity deaths within Ontario shelters more than tripled when comparing the pre-pandemic (n=48) with the pandemic period (n=162). Fentanyl directly contributed to the majority of these deaths, and its role as a direct contributor to death rose during the pandemic (from 85.4% to 94.4%; p=0.04), as did those of any stimulants (from 43.8% to 71.0%; p< 0.001). Moreover, benzodiazepine detection in opioid-related toxicity deaths increased during the pandemic (from 27.1% to 56.8%; p<0.001). In both the pre-pandemic and pandemic periods, more than half of the recorded deaths occurred among people with a diagnosis of an opioid use disorder (59.6% vs 53.5%; p=0.46), and a large percentage of people had a healthcare encounter in the week before death (46.8% vs 43.9%; p=0.73). Conclusions: Opioid-related toxicity deaths within Ontario's shelters have increased rapidly over the study period, with notable changes in the circumstances of death and patterns of non-pharmaceutical opioid involvement during the COVID-19 pandemic period. This study demonstrates the urgent need to expand programme and policy interventions tailored toward harm reduction within Ontario's shelter system.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".