Ranking the relative importance of COVID-19 immunisation strategies: a survey of expert stakeholders in Canada
Bibliographic record
Abstract
ABSTRACT Background In the face of anticipated limited COVID-19 vaccine supply necessitating the vaccination of certain groups earlier than others, the assessment of values and preferences of stakeholders is an important component of an ethically sound vaccine prioritisation framework. Objective To establish a preliminary expert stakeholder perspective on the relative importance of pandemic immunisation strategies for different COVID-19 pandemic scenarios at the time of initial COVID-19 vaccine availability. Methods A survey was conducted by an email process from July 22 to August 14, 2020. Stakeholders included clinical and public health expert groups, provincial and territorial committees and national Indigenous groups, patient and community advocacy representatives and experts, health professional associations, and federal government departments in Canada. Survey results were analysed using descriptive statistics. Results Of 156 stakeholders contacted, 74 surveys were completed for a participation rate of 47.4%. During an anticipated period of initial vaccine scarcity for all pandemic scenarios, stakeholders generally considered the most important immunisation strategy to be protecting those who are most vulnerable to severe illness and death from COVID-19. This was followed in importance by the strategies to protect healthcare capacity, and to minimise transmission of COVID-19. In this supply constrained context, an immunisation strategy to protect critical infrastructure was considered the least important. Conclusion The findings of this study provide a timely, preliminary Canadian expert perspective on priority COVID-19 pandemic immunisation strategies to guide early public health planning for an eventual COVID-19 immunisation program. These results fill a gap in the literature and could help advisory groups around the world in their assessment of values and preferences for ethical guidelines for COVID-19 vaccine allocation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".