Drug Overdoses During the COVID‐19 Pandemic Among Recently Homeless Individuals
Bibliographic record
Abstract
AIMS: To examine how weekly rates of emergency department (ED) visits for drug overdoses changed among individuals with a recent history of homelessness (IRHH) and their housed counterparts during the pre-pandemic, peak, and re-opening periods of the first wave of the COVID-19 pandemic, using corresponding weeks in 2019 as a historical control. DESIGN: Population-based retrospective cohort study conducted between September 30, 2018 and September 26, 2020. SETTING: Ontario, Canada. PARTICIPANTS: A total of 38 617 IRHH, 15 022 369 housed individuals, and 186 858 low-income housed individuals matched on age, sex, rurality, and comorbidity burden. MEASUREMENTS: ED visits for drug overdoses of accidental and undetermined intent. FINDINGS: Average rates of ED visits for drug overdoses between January and September 2020 were higher among IRHH compared with housed individuals (rate ratio [RR], 148.0; 95% CI, 142.7-153.5) and matched housed individuals (RR, 22.3; 95% CI, 20.7-24.0). ED visits for drug overdoses decreased across all groups by ~20% during the peak period (March 17 to June 16, 2020) compared with corresponding weeks in 2019. During the re-opening period (June 17 to September 26, 2020), rates of ED visits for drug overdoses were significantly higher among IRHH (RR, 1.56; 95% CI, 1.44-1.69), matched housed individuals (RR, 1.25; 95% CI, 1.08-1.46), and housed individuals relative to equivalent weeks in 2019 (RR, 1.07; 95% CI, 1.02-1.11). The relative increase in drug overdose ED visits among IRHH was larger compared with both matched housed individuals (P = 0.01 for interaction between group and year) and housed individuals (P < 0.001) during this period. CONCLUSIONS: Recently homeless individuals in Ontario, Canada experienced disproportionate increases in ED visits for drug overdoses during the re-opening period of the COVID-19 pandemic compared with housed people.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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 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".