Access to skilled attendant at birth and the coverage of the third dose of diphtheria-tetanus-pertussis vaccine across 14 West African countries – an equity analysis
Bibliographic record
Abstract
BACKGROUND: Universal Health Coverage (UHC) remains a critical public health goal that continues to elude many countries of the global south. As countries strive for its attainment, it is important to track progress in various subregions of the world to understand current levels and mechanisms of progress for shared learning. Our aim was to compare multidimensional equity gaps in access to skilled attendant at birth (SAB) and coverage of the third dose of Diphtheria-Tetanus-Pertussis (DTP3) across 14 West African countries. METHODS: The study was a cross sectional comparative analysis that used publicly available, nationally representative health surveys. We extracted data from Demographic and Health Surveys, and Multiple Indicator Cluster Surveys conducted between 2010 and 2017 in Benin, Burkina Faso, Cote d' Ivoire, The Gambia, Ghana, Guinea, Guinea Bissau, Liberia, Mali, Niger, Nigeria, Senegal, Sierra Leone and Togo. The World Health Organization's Health Equity Assessment Toolkit (HEAT Plus) software was used to evaluate current levels of intra-country equity in access to SAB and DTP3 coverage across four equity dimensions (maternal education, location of residence, region within a country and family wealth status). RESULTS: There was a general trend of higher levels of coverage for DTP3 compared to access to SAB in the subregion. Across the various dimensions of equity, more gaps appear to have been closed in the subregion for DTP3 compared to SAB. The analysis revealed that countries such as Sierra Leone, Liberia and Ghana have made substantial progress towards equitable access for the two outcomes compared to others such as Nigeria, Niger and Guinea. CONCLUSION: In the race towards UHC, equity should remain a priority and comparative progress should be consistently tracked to enable the sharing of lessons. The West African subregion requires adequate government financing and continued commitment to move toward UHC and close health equity gaps.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".