The cost‐effectiveness of screening blood donors for malaria by PCR
Bibliographic record
Abstract
BACKGROUND: The cost-effectiveness of four blood donor screening strategies for malaria was estimated to determine whether transmission by transfusion can be reduced. STUDY DESIGN AND METHODS: A decision analysis model was developed to compare 1) not screening allogeneic blood donors for malaria (Strategy 1); 2) using the standard questionnaire (Strategy 2); 3) using the standard questionnaire followed by testing blood donors with risk factors for malaria with PCR (Strategy 3); and 4) screening all blood donors using PCR (Strategy 4). The expected costs and the number of cases of malaria for each strategy were compared and incremental cost-effectiveness ratios were calculated as the cost per case of malaria averted. All costs are in Canadian dollars. RESULTS: Strategies 2 and 3 had the same effectiveness but different costs, with Strategy 3 being less costly. Compared to Strategy 1, the incremental cost effectiveness ratio was 6463 dollars per case of malaria averted for Strategy 3. Strategy 4 resulted in less transmission of malaria (0.4/million donors), but the cost compared to Strategy 3 was 3,972,624 dollars per case of malaria averted. CONCLUSION: The addition of PCR to the standard screening questionnaire is economically attractive compared to the current standard screening questionnaire.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".