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Record W2990741562 · doi:10.1111/vox.12867

HIV residual risk in Canada under a three‐month deferral for men who have sex with men

2019· article· en· W2990741562 on OpenAlex
Sheila F. O’Brien, Yves Grégoire, Josiane Pillonel, Whitney R. Steele, Brian Custer, Katy Davison, Marc Germain, Antoine Lewin, Clive R. Seed

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueVox Sanguinis · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBlood donation and transfusion practices
Canadian institutionsHéma-QuébecCanadian Blood Services
FundersCanadian Blood Services
KeywordsDeferralResidual riskHuman immunodeficiency virus (HIV)MedicineMen who have sex with menDemographyResidualInternal medicineFamily medicineEconomicsComputer science

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.416
Threshold uncertainty score0.765

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.015
GPT teacher head0.222
Teacher spread0.208 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it