Decreasing parvovirus <scp>B19</scp> and hepatitis A nucleic acid test positivity rates in Canadian plasma donors following the initiation of <scp>COVID</scp>‐19 restriction in March 2020
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: In Canada, plasma sent for fractionation is tested for both parvovirus B19 (B19V) and hepatitis A virus (HAV). This study compared positivity rates of B19 and HAV nucleic acid tests (NATs) in Canadian plasma samples for the pre-COVID-19 restriction era (2015 to end of February 2020 [Q1] 2020) and the post-COVID-19 restriction era. MATERIALS AND METHODS: Pooled EDTA plasma specimens were tested within 24 months of blood draw using the Procleix Panther System (Grifols Diagnostic Solutions Inc, San Diego, CA, USA) for B19V and HAV detection. Reactive pools were resolved by individual specimen testing. RESULTS: Between 1 January 2015, and 31 March 2022, 3,928,619 specimens from Canadian plasma donors were tested for B19V. For the same period, 3,922,954 specimens were tested for HAV. To account for a lag in specimen testing for up to 24 months, the data were divided into: (1) a pre-pandemic period (1 January 2015-31 March 2020; B19V tested n = 2,412,701, B19V NAT-positive n = 240 [0.01%], HAV tested n = 2,407,036, HAV NAT-positive n = 26 [0.001%]); (2) a two-year mixed-impact period (1 April 2020-31 March 2022; B19V tested n = 968,250, B19V NAT-positive n = 14 [0.001%], HAV tested n = 968,250, HAV NAT-positive n = 2 [0.0002%]); and (3) a pandemic-impact period (1 April 2022-31 March, 2023; B19V tested n = 597,668, B19V NAT-positive n = 3 [0.0005%], HAV tested n = 597,668, HAV NAT-positive n = 1 [0.0002%]). CONCLUSION: The percentage of B19V- and HAV-positive donations was significantly reduced from the pre-pandemic period to the pandemic-impact period.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".