Malaria blood safety policy in five non-endemic countries: a retrospective comparison through the lens of the ABO risk-based decision-making framework.
Bibliographic record
Abstract
BACKGROUND: In non-endemic countries, malaria risk is addressed by selectively testing or deferring at-risk donors. These policy decisions were made using a variety of decision-making frameworks prior to the development of the Alliance of Blood Operators Risk Based Decision-Making Framework. It is unclear whether the range of items assessed in the decision-making process would be increased if the Framework were used. We compared assessments considered in France, England and Australia for decisions to implement selective testing, plus donor selection criteria (Canada and the USA included) with those recommended by the Framework. MATERIALS AND METHODS: Elements of the Framework were identified: the intervention, safety threat, availability threat, donor impact, financial implications, risk communication, stakeholder and regulatory aspects. Decisions about selective testing and donor selection criteria were analysed separately. Assessments were compared against elements of the Framework and the level of concern for considerations rated. RESULTS: Sufficiency of the blood supply (plus safety in France) were the drivers for selective testing; main trade-offs were high operational impact and cost. In three donor criteria examples, transfusion-transmitted malaria cases prompted the change. Social concerns were high in France and Australia, political/regulatory concerns influenced decisions in France, Australia and Canada, while sufficiency was a consideration in Canada and the USA. Decision trade-offs involved moderate operational impact. DISCUSSION: The assessments considered in each country were generally consistent with the assessments recommended by the Framework. When data supported quantified risk assessment, safety and operational feasibility had the greatest weight. When risk was not well defined, contextual factors such as social and political concern had greater weight.
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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 | 0.009 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 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 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".