Human T‐cell lymphotropic virus: A simulation model to estimate residual risk with universal leucoreduction and testing strategies in Canada
Bibliographic record
Abstract
Background and Objectives In Canada, transfusion transmission risk of Human T‐cell lymphotropic virus ‐I/ II ( HTLV ) is addressed by universal leucoreduction and universal antibody testing. We aimed to estimate the risk with the current policy, if testing only first‐time donors and if testing were stopped. Materials and Methods Monte Carlo simulation was employed to estimate the proportion of red cell concentrate, random donor platelet and apheresis platelet units that would be released into inventory in each scenario (10 billion donors each). The model estimated the number of HTLV ‐positive donations not intercepted by testing, randomly assigned the number of HTLV particles/100 leucocytes using proportions from published data and randomly selected a postleucoreduction leucocyte count from quality control data. Units were considered infectious if ≥9 × 10 4 copies of HTLV provirus. Results With universal leucoreduction in place, the residual risk of releasing an HTLV potentially infectious unit with universal testing was 1 in 1·2 billion units (0, 1 in 55·9 million), with testing only first‐time donors 1 in 7·1 million (0, 1 in 1·05 million) and with no testing 1 in 1·0 million (0, 1 in 178 600). The efficacy of leucoreduction was >99·5% (lower bound 95·7%) for all scenarios. Conclusion With universal leucoreduction in place, switching from universal testing to testing first‐time donors would incur very low risk.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".