West Nile Virus positivity amongst Canadian blood donors and effectiveness of off‐season screening
Bibliographic record
Abstract
BACKGROUND: We sought to examine the prevalence of West Nile Virus (WNV) nucleic acid test (NAT) positivity over time in Canadian blood donors, examine the level of false-positive NAT screening, and understand the effectiveness of travel-related testing outside of WNV seasonality in Canada. STUDY DESIGN AND METHODS: All blood donations in Canada (except Québec) between 2018 and 2023 were tested by the Roche Cobas WNV-NAT assay during the summer-fall season by Canadian Blood Services. Testing for recent travel outside Canada was performed in the winter-spring season. All 2023 WNV-NAT-positives were confirmed by two independent WNV-specific polymerase chain reaction (PCRs). RESULTS: While WNV positivity varied by location and time, no increasing trend of positivity was observed over the 6-year study period. No WNV-NAT-positive donors with a history of recent travel outside of Canada in the winter-spring season were identified by donor screening (2018-2023). In total, 2,454,102 samples were tested during summer months and 267,988 in winter months. In 2023, WNV-specific PCR confirmed 10 of 13 (76.9%) screening WNV-NATs. Recent Japanese Encephalitis Virus (JEV) vaccination was identified as a potential false positive for initial WNV screening results. DISCUSSION: Between 2018 and 2023, WNV-NAT positivity amongst Canadian blood donors remained stable, with no evidence of an increasing positivity trend. The utility of off-season travel-related testing may be limited, as no donors were identified during the six-year study timeframe. Finally, confirmation testing using WNV-specific PCR is recommended to identify true cases and to limit misidentification of other genetically similar viruses, such as JEV.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".