Health actor approaches to financing universal coverage strategies for pneumococcal and rotavirus immunisation programmes in low-income and middle-income countries: a scoping review protocol
Bibliographic record
Abstract
INTRODUCTION: Sustainable financing of immunisation programmes is an important step towards universal coverage of life-saving vaccines. Yet, financing mechanisms for health programmes could have consequences on the design of universal approaches to immunisation coverage. Effective implementation of immunisation interventions necessitates investigating the roles of institutions and power on interventions. This review aims to understand how sustainable financing and equitable immunisation are conceptualised by health actors like Gavi, and government-related entities across low-income and middle-income countries (LMICs) and how financing mechanisms can affect universal coverage of vaccines. METHODS AND ANALYSIS: This study protocol outline a scoping review of the peer-reviewed and the grey literature, using established methodological framework for scoping review. Literature will be identified through a comprehensive search of multiple databases and grey literature. All peer-reviewed implementation research studies from the year 2002 addressing financing and universal coverage of immunisation programmes for the pneumococcal conjugated vaccine and rotavirus vaccines immunisation interventions will be included and grey literature published in/after the year 2015. For the study scope, population, concept and context are defined: Population as international and national health stakeholders financing immunisation programmes; Concept as implementation research on pneumococcal conjugate and rotavirus vaccination interventions; and Context as LMICs. Findings will be quantitatively summarised to provide an overview and narratively synthesised and analysed. Studies that do not use implementation research approaches, frameworks or models will be excluded. ETHICS AND DISSEMINATION: Ethics approval is not required for this scoping review. Findings and recommendations will be presented to implementation researchers and health stakeholders.
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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 | 0.127 | 0.106 |
| Meta-epidemiology (narrow) | 0.004 | 0.004 |
| Meta-epidemiology (broad) | 0.008 | 0.013 |
| Bibliometrics | 0.020 | 0.016 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.007 | 0.009 |
| Research integrity | 0.010 | 0.006 |
| Insufficient payload (model declined to judge) | 0.061 | 0.013 |
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".