Effect of seasonal influenza vaccination on influenza symptom severity among children in Hutterite communities: Follow‐up study of a randomized trial
Bibliographic record
Abstract
BACKGROUND: We investigated whether influenza vaccination reduces symptom severity among children who develop laboratory-confirmed influenza, and whether this association differed between influenza vaccine formulations. METHODS: We performed a retrospective cohort study using data from two blinded cluster randomized control trials of influenza vaccines in Hutterite colonies. In trial 1, children received trivalent inactivated influenza vaccine (TIV) or hepatitis A vaccine. In trial 2, children received trivalent live attenuated (TLAIV) or TIV. We assessed four outcomes (total number of symptoms, number of respiratory symptoms, number of systemic symptoms, and duration of symptoms) among children with PCR-confirmed influenza. We utilized two-sample t tests to quantify the relationship between vaccine group and outcome. We performed multivariable strain-specific analyses, controlling for age and season. RESULTS: TIV vs. Hep A vaccine: Among vaccinated children, 200 confirmed influenza infections were observed across 3014 person-seasons. Vaccine type (TIV vs. Hep A vaccine) did not significantly affect the number of respiratory or systemic symptoms, nor duration of symptoms (P > .05). TLAIV vs. TIV: Among 1186 children who received a study vaccine, 166 confirmed influenza infections were observed. TLAIV recipients experienced fewer total, respiratory, and systemic symptoms compared to TIV recipients (P < .05 for all). TLAIV-associated attenuation of symptom severity was observed in influenza B or A/H1N1 infections, but not H3. CONCLUSIONS: Seasonal influenza vaccine did not consistently attenuate symptom severity in the context of vaccine failure; however, TLAIV offered superior severity attenuation compared to TIV. Our results challenge the dictum that influenza vaccine reduces the severity of symptoms even when the vaccine fails to prevent influenza.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".