Relative efficacy of nucleic acid amplification testing and serologic screening in preventing hepatitis C virus transmission risk in seven international regions
Bibliographic record
Abstract
BACKGROUND: The relative contribution of serologic screening and nucleic acid testing (NAT) to prevent hepatitis C virus (HCV) transmission has not been rigorously addressed. STUDY DESIGN AND METHODS: Twenty-one blood organizations in seven geographical regions performing individual-donation (ID)-NAT in parallel with anti-HCV screening provided data from 10,897,105 donations to establish HCV infection rates in first-time, lapsed, and repeat donations. Screening efficacy was modeled for: anti-HCV alone, HCV antigen/antibody (combo), minipool (MP)-NAT in pools of 8 and 16 with anti-HCV, ID-NAT and anti-HCV, and ID-NAT alone. Probabilities of infectivity for red blood cell transfusions were estimated as 100% from window period (WP) and concordant HCV RNA/antibody-positive (concordantly positive [CP]) donations and 0.028% from anti-HCV-positive and RNA-negative probable resolved (PR) donations. RESULTS: There were 5146 confirmed infections (30 WP, 3827 CP, and 1289 PR). Infection rates and transmission risks varied substantially across regions and by donation status. Residual risk with ID-NAT and serology screening was estimated at one in 250,000 in Egypt and at one in 10,000,000 in other regions combined; risk would increase to one in 7300 and one in 312,000, respectively, if NAT had not been performed. ID-NAT with or without anti-HCV testing showed higher efficacy than either MP-NAT or combo assays, particularly in lapsed or repeat donors in whom 99.2, 98.5, and 93.2% of infectious donations were estimated to be interdicted by these respective testing strategies. CONCLUSIONS: The incremental efficacy of anti-HCV testing when ID- NAT screening is performed was minimal, particularly for screening lapsed and repeat donations.
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.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".