Comparison of whole blood on filter strips with serum for avian influenza virus antibody detection in wild birds
Bibliographic record
Abstract
Abstract Serological surveillance enhances our understanding of influenza A virus (IAV) exposure and dynamics in wild bird populations. Traditional serum-based testing, while effective, poses logistical challenges for large-scale surveillance, particularly in remote regions, for small-bodied species or in scenarios such as hunter-harvested samples where serum collection can be impractical. This study evaluates the use of whole blood collected on high-quality cellulose filter strips as an alternative to serum for detecting antibodies against IAV nucleoprotein (NP) and hemagglutinin (HA) H5 and H7 targets. We tested paired serum and whole blood on filter strips collected from wild birds using the commercially available IDEXX AI MultiS Screen Ab test and in-house competitive enzyme-linked immunosorbent assays (ELISAs) developed at the National Centre for Foreign Animal Disease (NCFAD) of the Canadian Food Inspection Agency. Strong correlations (ρ = 0.77) were observed between serum and whole blood on filter strips for NP detection with the IDEXX ELISA, while moderate correlations were noted for NCFAD’s NP (ρ = 0.58) and H5 (ρ = 0.65) assays. Correlation between serum and whole blood on filter strips for NCFAD’s H7 assay was poor, although interpretation is limited due to the small sample size of H7 positives. Threshold optimization using the Youden index improved diagnostic performance, with optimized cutoffs identified for NP (sample-to-negative < 0.7708 for IDEXX and percentage inhibition [PI] > 39.56 for NCFAD) and H5 (PI > 20.37). Storage conditions impacted performance, with frozen whole blood on filter strips achieving higher sensitivity compared to those stored at room temperature. These findings support the use of filter strips to collect whole blood as an informative alternative for IAV serological surveillance in wild birds when serum is unavailable, provided optimal storage conditions and threshold adjustments are implemented, although serum remains the superior sample type.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".