Aspects of Prophylactic Vaccination against Cervical Cancer and Other Human Papillomavirus-Related Cancers in Developing Countries
Bibliographic record
Abstract
Cervical cancer and other human papillomavirus- (HPV-) related cancers are preventable, but preventive measures implemented in developing countries and especially in low-income rural regions have not been effective. Cervical cancer burden derived from sexually transmitted HPV infections is the heaviest in developing countries, and a dramatic increase in the number of cervical cancer cases is predicted, if no intervention is implemented in the near future. HPV vaccines offer an efficient way to prevent related cancers. Recently implemented school-based HPV vaccination demonstration programmes can help tackle the challenges linked with vaccine coverage, and access to vaccination and health services, but prevention strategies need to be modified according to regional characteristics. In urban regions WHO-recommended vaccination strategies might be enough to significantly reduce HPV-related disease burden, but in the rural regions additional vaccination strategies, vaccinating both sexes rather than only females when school attendance is the highest and applying a two-dose regime, need to be considered. From the point of view of both public health and ethics identification of the most effective prevention strategies is pivotal, especially when access to health services is limited. Considering cost-effectiveness versus justice further research on optional vaccination strategies is warranted.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".