Impacts of the COVID-19 pandemic on supervised consumption service delivery in Vancouver and Surrey, Canada from the perspective of service providers
Bibliographic record
Abstract
Following the onset of the COVID-19 pandemic, an ever-increasing number of people have died from the toxic drug supply in Canada. Emerging evidence suggests that reduced access to harm reduction services has been a contributing factor. However, the precise impacts of the pandemic on supervised consumption service (SCS) delivery have not been well characterized. The present study sought to explore the impacts of the pandemic on SCS delivery in Vancouver and Surrey, Canada. Between October 2021 and March 2022, in-depth, semi-structured interviews were conducted with staff from two SCS: SafePoint in Surrey (n = 12) and Insite in Vancouver (n = 9). Thematic analysis focused on key changes to SCS delivery after the emergence of the COVID-19 pandemic, with a focus on associated challenges and emergent staff responses. Participants described key challenges as: capacity restrictions hindering service access and compromising care quality; exclusion of frontline staff perspectives from evolving SCS policy and practice decision-making; intensified power dynamics between staff and service users; and modified overdose response procedures, combined with a rise in complex overdose presentations, undermining service accessibility and quality. Emergent staff responses to these challenges included: collective staff organizing for changes to policy; individual frontline staff non-compliance with emerging policies; and staff experiencing burnout in their roles. This study highlights how COVID-19-related changes to service delivery produced challenges for SCS staff and service users, while identifying strategies employed by staff to address these challenges. Additionally, the findings point to opportunities to improve care for people who use drugs during intersecting public health crises.
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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 | 0.001 |
| 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".