179:oral Priority-setting for effective pandemic preparedness: a case study of priority setting for COVID-19 in the Western Pacific Region
Bibliographic record
Abstract
Background There have been divergent approaches used by countries to curb and control the spread, impact and burden of COVID-19. While priority setting – defined as decision-making about the allocation of resources between competing claims of different services, populations and elements of care – is recognized as critical for promoting accountability and transparency in health system planning, its role in supporting rational, equitable and fair pandemic preparedness planning is less well understood. Our multi-country project investigates the effectiveness of priority setting for pandemic preparedness planning. This study aims to describe how priority setting guided the COVID-19 responses implemented in the sub-set of countries in the Western Pacific Region. Methods Guided by the adapted Kapiriri and Martin Framework, we purposively sampled a subset of countries in the WHO Western Pacific Region (WPRO) and undertook a critical document review of national-level pandemic preparedness plans. A pre-specified, validated tool guided data extraction on twenty quality parameters of PS. A critical synthesis was completed. Results Nine plans were included (41% WPRO countries), including: Papua New Guinea, Tonga, Philippines, Fiji, China, Australia, New Zealand, Japan, and Taiwan. There was evidence of strong political will to quickly and effectively combat the pandemic. With 8/9 countries being islands, an emphasis on securing boarders was reflected in the plans. A limited number of quality indicators of effective priority setting were described. Most commonly, plans described resource needs (n=8), stakeholder engagement (n=8), and responsibilities of legitimate institutions (n=7). Consideration of health inequalities, fair financial burden, or public engagement/acceptance of priorities was not evident in any plans. Discussion This project advances understanding of how priority setting has been used in the WPRO region to support COVID-19 responses. It provides a basis for examining the relationship between effective priority setting for pandemic preparedness and country-level outcomes in future work.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".