COVID-19 and substance use disorders: a review of international guidelines for frontline healthcare workers of addiction services
Bibliographic record
Abstract
BACKGROUND: People with substance use disorders may be at a greater risk of contracting COVID-19 infection and developing medical complications. Several institutional and governmental health agencies across the world developed ad hoc guidance for substance use disorder services and care of individuals misusing substances. We aimed to synthesise the best available recommendations on management and care of people with or at risk of substance use disorders during the COVID-19 pandemic from existing guidelines published in UK, USA, Australia, Canada, New Zealand, and Singapore. METHODS: 2021). We summarized the extracted data as answers to specific clinical questions. RESULTS: We organised the available recommendations from 19 sources in three sections. First, we focused on general advice and recommendations for people who misuse alcohol or drugs during the COVID-19 pandemic, the design of contingency plans, safeguarding issues for children and families of service users and advice to the public, patients, and carers. Then, we summarised specific guidelines for people who use illicit drugs and related services, such as opioid substitution treatment and needle and syringe programmes. Finally, we provided a synthesis on specific recommendations for services supporting people who misuse alcohol and key topics in the field, such as management of alcohol detoxification and safe transition between supervised and unsupervised consumption. CONCLUSIONS: Available guidance reflected different approaches, ranging from being extremely cautious in providing recommendations other than generic statements to proposing adaptation of previously available guidelines to confront the challenges of the COVID-19 pandemic. After the early phase, guidance focused on reduction of infection transmission and service delivery. Guidance did not provide advice on infection prevention via vaccination programmes and service access strategies tailored to individuals with substance use disorders.
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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 | 0.022 | 0.062 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.016 | 0.014 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".