South Africa regains polio-free status: Processes involved and lessons learnt
Bibliographic record
Abstract
The World Health Organization recommends continuous immunisation coverage and polio surveillance standards for countries to sustain a polio-free status. We highlight experiences and lessons learnt by South Africa (SA) in losing – and subsequently regaining – its polio-free status. Following some decline in achieving acute flaccid paralysis surveillance and immunisation coverage targets, SA had its polio-free status withdrawn in 2017. Existing gaps were addressed and the polio-free status was regained in 2019. Lessons learnt from this experience include reaffirming the importance of continued commitment to polio eradication efforts, strengthening health systems through quality improvement projects, ensuring accountability in supervision, and monitoring of polio-related indicators. Consistent political commitment, collaboration and accountability are critical in sustaining the country’s health programmes, including maintaining a polio-free status and closing identified 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 | 0.030 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.013 |
| Scholarly communication | 0.013 | 0.014 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.005 | 0.014 |
| Insufficient payload (model declined to judge) | 0.004 | 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".