Ranking the relative importance of COVID-19 vaccination strategies in Canada: a priority-setting exercise
Bibliographic record
Abstract
BACKGROUND: When vaccine supplies are anticipated to be limited, 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 prioritization framework. The objective of this study was to conduct a priority-setting exercise to establish an expert stakeholder perspective on the relative importance of COVID-19 vaccination strategies in Canada. METHODS: The priority-setting exercise included a survey of stakeholders that was conducted from July 22 to Aug. 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. Survey results were analyzed to identify trends. RESULTS: Of 155 stakeholders contacted, 76 surveys were received for a participation rate of 49%. During a period of anticipated initial vaccine scarcity for all pandemic scenarios, stakeholders generally considered the most important vaccination strategy to be protecting those who are most vulnerable to severe illness and death from COVID-19. This was followed in importance by strategies to protect health care capacity, minimize transmission of SARS-CoV-2 and protect critical infrastructure. INTERPRETATION: This priority-setting exercise established that there is general alignment in the values and preferences across stakeholder groups: the most important vaccination strategy at the time of limited initial vaccine availability is to protect those who are most vulnerable. The findings of this priority-setting exercise provided a timely expert perspective to guide early public health planning for COVID-19 vaccines.
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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 | 0.025 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.011 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".