Covid-19: Lessons from the pandemic in sub-Saharan Africa relevant to the WHO IA2030 vaccination agenda
Bibliographic record
Abstract
While the global need to promote vaccination against viral illnesses is recognized, there are fundamental reasons for the failure of many programs. The World Health Organization has emphasized that the causes of low vaccine use must be understood and addressed in order to increase people’s demand for immunization services, and such understanding is central to promoting vaccine acceptance, as called for in the current WHO IA2030 initiative. Immunization programs remain fundamental to both pandemic preparedness and robust health systems. But, to achieve the goals of IA2030 requires improved targeting and reach to protect against viral illness and other global pathogens, hence the need for creative and innovative community engagement to increase vaccine uptake, and the relevance of learning from past pandemics. In sub-Saharan Africa, important lessons were learned during the Covid-19 pandemic; many of these are now broadly applicable to enhance current programs to promote vaccine acceptance such as the WHO IA2030 initiative. Strategies that helped increase vaccine uptake in Africa included six approaches to health promotion called for by the 2017 Lancet Commission on the future of health in sub-Saharan Africa. (Adoption of a community empowerment approach; Use of inclusive, people-centered strategies; Provision of innovative education; Creation of novel and improved tools; Training personnel to be mindful of, and responsive to, local needs; and Endorsement of non-traditional avenues to engage and inform). This commentary describes the principles underlying these six approaches, and summarizes ways in which their use contributed to programs working to increase vaccine uptake in sub-Saharan Africa that are applicable in a global context.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".