Comparative Immunogenicity of the 2014–2015 Northern Hemisphere Trivalent IIV and LAIV against Influenza A Viruses in Children
Bibliographic record
Abstract
Both inactivated influenza vaccines (IIV) and live-attenuated influenza vaccines (LAIV) have been recommended for administration to children. Children are a high-risk group for severe influenza, and a major source of transmission. Therefore, prevention of infection by vaccination is particularly important. However, efficacy and immunogenicity of these vaccines are known to vary by season and geographic location. We compared the immunogenicity of the 2014-2015 Northern Hemisphere trivalent IIV and LAIV against influenza A virus in Canadian Hutterite children aged 2 to 17 using hemagglutination inhibition (HAI) assays, and enzyme-linked immunosorbent assays to measure hemagglutinin-specific serum IgA and mucosal IgA. Both vaccine formulations induced significant increases in HAI titers against H1N1 and H3N2 vaccine strains. Serum IgA titers against H3N2 were significantly boosted by both IIV and LAIV, while only IIV induced a significant increase in serum IgA specific to the H1N1 vaccine strain. While HAI titers correlated with protection conferred by IIV, mucosal IgA titers correlated with protection conferred by LAIV (mucosal IgA titers could not be established as a correlate for IIV due to sample size limitations). IIV and LAIV were previously reported to be equally efficacious in this cohort, although the immunogenicity of IIV was generally superior.
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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 | 0.001 |
| 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) | 0.001 | 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".