Minipool testing for <scp>SARS‐CoV</scp>‐2 <scp>RNA</scp> in United States blood donors
Bibliographic record
Abstract
BACKGROUND: SARS-CoV-2 RNA prevalence in blood donors from large geographic areas of high community transmission is limited. We tested residual donor plasma minipools (MPs) to determine SARS-CoV-2 RNAemia prevalence in six United States areas. STUDY DESIGN/METHODS: Blood donations collected from 7 March 2020 to 25 September 2020 were tested for SARS-CoV-2 RNA (vRNA) in MP of 6 or 16 donations using the Grifols Procleix SARS-CoV-2 research-use only (RUO) transcription-mediated amplification (TMA) assay. Reactive results were confirmed using an alternate target region TMA assay. Reactive MPs were tested by TMA after serial dilution to estimate viral load. Testing for anti-SARS-CoV-2 antibodies and infectivity was performed. RESULTS: A total of 17,995 MPs corresponding to approximately 258,000 donations were tested for vRNA. Three confirmed reactive MP16 were identified. The estimated prevalence of vRNA reactive donations was 1.16/100,000 (95% CI 0.40, 3.42). The vRNA-reactive samples were non-reactive for antibody, and the estimated viral loads of the (presumed single) positive donations within each MP ranged from <1000 to <4000 copies/ml. When tested, no infectivity was observed in inoculated permissive cell cultures. DISCUSSION: Blood donation MP-nucleic acid testing (NAT) indicated that SARS-CoV-2 RNAemia is infrequent and, when detected, the vRNA was at low concentrations. Only one RNA-reactive MP could be tested for infectivity for operational reasons and was not infectious in cell culture. These findings support current recommendations from international and national regulatory agencies to not screen donors by NAT.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".