The 2003 West Nile virus United States epidemic: the America's Blood Centers experience
Bibliographic record
Abstract
BACKGROUND: A detailed assessment of West Nile virus (WNV) yield is needed to evaluate the effectiveness of the WNV nucleic acid amplification technology (NAT) screening implemented in 2003. STUDY DESIGN AND METHODS: WNV NAT screening and donation data were compiled from members of America's Blood Centers, which collect nearly 50 percent of the US blood supply. WNV RNA screening was performed with either the Gen-Probe/Chiron Procleix transcription-mediated amplification assay or the Roche TaqScreen polymerase chain reaction. Results of alternate NAT and WNV immunoglobulin M (IgM) antibody assays conducted on index and follow-up samples were obtained from test manufacturers. Presumed WNV positivity was based on NAT repeat reactivity of the individual index donation whereas confirmatory status was based on additional IgM testing of the index donation and NAT and serology testing of follow-up samples. RESULTS: From July through October 2003, 2.5 million donations were screened for WNV RNA. Of 877 NAT-reactive donations (screening positivity rate of 3.5 per 10,000 units), 430 (49%) were confirmed positive, whereas 68 (8%) lacking follow-up data remained presumed positive. The sensitivity and positive predictive value of a presumed viremic result relative to final confirmatory status were 92 and 99 percent, respectively. WNV activity was highest in the central plains with prevalence per 10,000 peaking August 1 to 15 in Colorado (67.7) and South Dakota (77.5) and August 16 to 31 in Wyoming (74.1) and North Dakota (102.0). CONCLUSIONS: WNV screening interdicted many viremic units, thereby reducing transfusion-transmitted infections. This study demonstrates that a national collaborative effort facilitates timely surveillance of blood donor infectious disease prevalence rates.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".