Supporting Self-isolation for COVID-19 With “Risk Mitigation” Prescribing and Housing Supports for People Who Use Drugs: A Case Report
Bibliographic record
Abstract
BACKGROUND: Self-isolation is critical in preventing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission. However, people who use drugs face significant barriers in adhering to the regulations. As a response, several supportive measures have been introduced in British Columbia, including temporary housing access and "risk mitigation" prescribing, in which health care providers prescribe pharmaceutical alternatives to the unregulated drug supply to prevent withdrawal and reduce overdose risk. CASE SUMMARY: We present a case of a 39-year-old male with a history of polysubstance use and frequent overdoses, who had tested positive for SARS-CoV-2 and was able to successfully self-isolate. "Risk mitigation" prescribing, supportive housing, and harm reduction services were initiated for his self-isolation and connection to community outreach teams for ongoing support. DISCUSSION: This case illustrates how "risk mitigation" prescribing supported patient's self-isolation, reduced his illicit drug use, and offered an opportunity for healthcare engagement. Access to safer alternatives to the toxic drug supply should continue beyond COVID-19 pandemic to address the persistent issues of contaminated drug supply and the overdose crisis in North America.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".