Development of WHO Recommendations for the Final Phase of Elimination and Prevention of Re-Establishment of Malaria
Bibliographic record
Abstract
The WHO recommends that all affected countries work toward the elimination of malaria, even those still experiencing a high burden of disease. However, malaria programs in the final phase of elimination or those working to prevent re-establishment of transmission after elimination could benefit from specific evidence-based recommendations for these settings as part of comprehensive and quality-controlled malaria guidelines. The WHO convened an external guideline development group to formulate recommendations for interventions to reduce or prevent malaria transmission in areas with very low- to low-transmission levels and those that have eliminated malaria. In addition, several interventions that could be deployed in higher burden areas to accelerate elimination, such as mass drug administration, were reviewed. Systematic reviews were conducted that synthesized and evaluated evidence for the benefits and harms of public health interventions and summarized critical contextual factors from a health systems perspective. A total of 12 recommendations were developed, with five related to mass interventions that could be deployed at higher transmission levels and seven that would be most appropriate for programs in areas close to elimination or those working to prevent re-establishment of transmission. Four chemoprevention, two active case detection, and one vector control interventions were positively recommended, whereas two chemoprevention and three active case detection interventions were not recommended by the WHO. None of the recommendations were classified as strong given the limited and low-quality evidence base. Approaches to conducting higher quality research in very low- to low-transmission settings to improve the strength of WHO recommendations are discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.063 | 0.132 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.010 |
| Bibliometrics | 0.014 | 0.008 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.010 | 0.005 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".