HIV residual risk in Canada under a three‐month deferral for men who have sex with men
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: In Canada, the deferral for men who have sex with men (MSM) was decreased from a permanent deferral to a 5-year then a 12-month deferral. Current HIV testing can detect an HIV infection in donated blood within 2 weeks of exposure; thus, a 12-month deferral may be unnecessarily restrictive. We aimed to estimate the residual risk of HIV if the deferral were further decreased to 3 months. MATERIALS AND METHODS: Using a deterministic model with stochastic Monte Carlo simulation, residual risk of HIV was the sum of testing error, assay sensitivity and window-period risks. Data inputs were estimated from donor surveillance, donor surveys and published data. Residual risk was modelled at baseline and using three scenarios: (1) most likely - non-compliance, HIV prevalence and incidence rates of MSM are unchanged; (2) optimistic - non-compliance improves by 50%; and (3) pessimistic - non-compliance, HIV prevalence and incidence rates of MSM all double. RESULTS: HIV residual risk at baseline was 1 in 36·0 million donations (95% CI 1 in 1 504 907 million, 10·5 million); in the most likely scenario 1 in 34·2 million (1 in 225 534 million, 8·7 million); in the optimistic scenario 1 in 36·0 million (1 in 282 618 million, 9·5 million); in the pessimistic scenario 1 in 16·7 million (1 in 39 469 million, 6·0 million). All confidence intervals overlapped. CONCLUSION: With very low modelled risk under a 12-month deferral, the additional risk with a 3-month deferral is very low. This is true even with a pessimistic scenario.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".