Serological Response to Influenza Vaccination among Children Vaccinated for Multiple Influenza Seasons
Bibliographic record
Abstract
BACKGROUND: To evaluate if, among children aged 3 to 15 years, influenza vaccination for multiple seasons affects the proportion sero-protected. METHODOLOGY/PRINCIPAL FINDINGS: Participants were 131 healthy children aged 3-15 years. Participants were vaccinated with trivalent inactivated seasonal influenza vaccine (TIV) over the 2005-06, 2006-07 and 2007-8 seasons. Number of seasons vaccinated were categorized as one (2007-08); two (2007-08 and 2006-07 or 2007-08 and 2005-06) or three (2005-06, 2006-07, and 2007-08). Pre- and post-vaccination sera were collected four weeks apart. Antibody titres were determined by hemagglutination inhibition (HAI) assay using antigens to A/Solomon Islands/03/06 (H1N1), A/Wisconsin/67/05 (H3N2) and B/Malaysia/2506/04. The proportions sero-protected were compared by number of seasons vaccinated using cut-points for seroprotection of 1:40 vs. 1:320. The proportions of children sero-protected against H1N1 and H3N2 was high (>85%) regardless of number of seasons vaccinated and regardless of cut-point for seroprotection. For B Malaysia there was no change in proportions sero-protected by number of seasons vaccinated; however the proportions protected were lower than for H1N1 and H3N2, and there was a lower proportion sero-protected when the higher, compared to lower, cut-point was used for sero-protection. CONCLUSION/SIGNIFICANCE: The proportion of children sero-protected is not affected by number of seasons vaccinated.
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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 | 0.002 |
| 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 | 0.001 |
| 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".