An evaluation of WHO emergency guidelines for Zika virus disease
Bibliographic record
Abstract
BACKGROUND: In the face of an unclear causal association between Zika virus in utero exposure and congenital abnormalities and urgent demand for guidance, the World Health Organization (WHO) had to produce timely and trustworthy guidelines during the 2016 Public Health Emergency of International Concern (PHEIC). METHODS: This is a cross-sectional evaluation of WHO emergency guidelines produced during the Zika virus disease PHEIC from 1 February to 18 November 2016. We assessed adherence to WHO publication requirements and the reporting of guideline development processes associated with trustworthiness. In the absence of quality appraisal tools for guidelines developed under compressed timeframes, we applied the Appraisal of Guidelines for Research and Evaluation (AGREE II) tool. RESULTS: We included 21 guidelines (13 de novo and 8 updates). Six guidelines used a formal evidence review process. Most guidelines involved external experts in the development process and collected declarations of interest. Peer review was reported in six documents. Most emergency guidelines included updating plans. The highest scoring AGREE II domain was clarity of presentation (median score 78%); the lowest scoring domain was applicability (median score 18%). CONCLUSION: WHO developed moderate- to high-quality emergency guidelines in the challenging context of a PHEIC. We found improvement opportunities for WHO guideline development teams in the use of evidence to formulate recommendations, the collection of declarations of interest, reporting of conflicts of interest, and the use of existing WHO organizational quality assurance processes.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Metaresearch Domain: Evaluation · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | medium |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Other design | high |
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 | 0.358 | 0.668 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.018 | 0.015 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".