Operating an overdose prevention site within a temporary emergency shelter during the COVID-19 pandemic
Bibliographic record
Abstract
SETTING: A temporary emergency shelter was established inside the Commonwealth Stadium in Edmonton, Alberta, to reduce COVID-19 transmission and mitigate health risks among people experiencing homelessness. INTERVENTION: A non-profit organization, Boyle Street Community Services, opened an overdose prevention site (OPS) between February and March 2022 inside the temporary emergency shelter. People accessed the shelter-based OPS to consume unregulated drugs (via injection, intranasally, or orally), receive medical aid, access sterile drug use equipment, and be connected to additional health and social supports, without leaving the shelter. We conducted short interviewer-administered surveys with OPS participants to examine participant views and identify suggested improvements. OUTCOMES: The shelter-based OPS was accessed a total of 1346 times by 174 unique people. Fentanyl was the most common self-reported drug consumed (59%) and most consumption (99% of episodes) was by injection. OPS staff responded to 66 overdoses and reported no deaths. Survey respondents reported that the shelter-based OPS was convenient, with no need to forfeit their shelter spot or find transportation to another OPS. Respondents indicated that the OPS felt safe and accessible and reported that it reduced drug use in other shelter areas. Participants identified the OPS' exclusion of inhalation as a limitation. IMPLICATIONS: People who use unregulated drugs and are experiencing homelessness are at a higher risk of negative health outcomes, which COVID-19 exacerbated. Integrating temporary shelter/housing and harm reduction services may be an innovative way to lower barriers, increase accessibility, and improve well-being for this structurally vulnerable population. Future operators should consider incorporating inhalation services to further reduce service gaps.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.009 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".