Building health system resilience in the context of primary health care revitalization for attainment of UHC: proceedings from the Fifth Health Sector Directors’ Policy and Planning Meeting for the WHO African Region
Bibliographic record
Abstract
BACKGROUND: The recent 2018 Declaration of Astana recognized primary health care (PHC) as a means to achieve universal health coverage (UHC) and the health-related Sustainable Development Goals (SDGs). Following this declaration, country progress on operationalization of the PHC agenda and attainment of UHC has been stalled by the new challenges posed by the COVID-19 pandemic. The pandemic has also disrupted the continuity of essential health service provision and tested the resilience of the region's health systems. METHODS: In accordance with this, the WHO Regional Office for Africa convened the Fifth Health Sector Directors' Planning and Policy Meeting across the 47 Member States of the Region. The two-day forum focused on building health system resilience to facilitate service continuity during health threats, PHC revitalization, and health systems strengthening towards UHC. RESULTS: The Regional Forum provided evidence on building resilient health systems in the WHO African Region and engaged participants in meaningful and critical discussion. It is from these discussions that four key themes emerged: (1) working multisectorally/intersectorally, (2) moving from fragmentation to integration, (3) ensuring implementation and knowledge exchange, and (4) rethinking resilience and embracing antifragility. These discussions and associated groupings by thematic areas lend themselves to recommendations for the WHO. CONCLUSIONS: This paper details the proceedings and key findings on building resilient health systems, the four themes that emerged from participant deliberation, and the recommendations that have emerged from the meeting. Deliberations from the Regional Forum are critical, as they have the potential to directly inform policy and program design, given that the meeting convenes health sector technocrats, who are at the helm of policy design, action, and implementation.
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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 | 0.050 | 0.033 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.018 | 0.007 |
| Scholarly communication | 0.014 | 0.006 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.010 | 0.014 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".