Real-World Effectiveness of Live Attenuated vs. Inactivated Influenza Vaccines in Children
Bibliographic record
Abstract
Abstract Background and objectives Quadrivalent live attenuated influenza vaccines (LAIV-4) offer an alternative to inactivated influenza vaccines (IIV) for children aged 2-17 years, but data on their comparative effectiveness are limited. This study assessed vaccination rates and real-world effectiveness of LAIV-4 and IIV in preventing influenza and influenza-like illness (ILI) in Italian children during the 2022-2023 and 2023-2024 seasons. Methods We conducted a population-based cohort study of children aged 2-14 years from September 2022 to April 2024, using data from Pedianet, a pediatric primary care database of anonymized records from family pediatricians. Children vaccinated with LAIV-4 or IIV were compared to unvaccinated children. The primary outcome was any first influenza or ILI episode. Monthly vaccination incidence rates per 1,000 person-months were calculated for each vaccine type. Hazard ratios (HRs) and their 95% confidence intervals (CIs) for vaccine effectiveness (VE) were estimated using adjusted mixed-effects Cox models. Results A total of 65,545 (472,173 person-months) and 72,377 (527,348 person-months) children were included for the 2022-2023 and 2023-2024 seasons, respectively. Vaccination rates were 12.71 and 12.85 per 1,000 person-months, respectively. Compared to unvaccinated children, LAIV-4 had an overall effectiveness of 43% (95% CI, 32%-53%), while IIV effectiveness was 54% (95% CI, 46%-61%). In 2022-2023, LAIV-4 (38% [95% CI, 12%-56%]) and IIV (49% [95% CI, 37%-58%]) had comparable effectiveness. In 2023-2024, LAIV-4 (40% [95% CI, 25%-52%]) was slightly less effective than IIV (58% [95% CI, 44%-68%])(p=0.048). Conclusions An overall moderate, comparable effectiveness of LAIV-4 and IIV in preventing influenza/ILI among Italian children was observed. Article Summary A retrospective population-based cohort analysis showing moderate effectiveness of live attenuated influenza vaccines (LAIVs) in preventing influenza/influenza-like-illness in Italian children. What’s Known on This Subject There is conflicting evidence on the effectiveness of the quadrivalent live attenuated influenza vaccine LAIV (LAIV-4) in the pediatric population. What This Study Adds This population-based study assesses the effectiveness of LAIVs against influenza/influenza-like illness (ILI) among children in Italy in the post-COVID-19 influenza seasons using real-world data. Our findings document moderate protection provided by LAIVs against influenza/ILI in the 2022-2023 and 2023-2024 seasons. Contributors Statement Page Dr. Vera Rigamonti performed the statistical analysis, interpreted the results, and drafted the initial manuscript; Dr. Vittorio Torri conceptualized and designed the artificial intelligence algorithms; Dr. Daniele Donà contributed to data interpretation; Drs Anna Cantarutti and Costanza Di Chiara, designed the study, contributed to the analysis plan, interpreted the results, supervised the project, and contributed to the manuscript writing; Profs. Shaun K Morris, Francesca Ieva, and Carlo Giaquinto interpreted the results and critically reviewed the manuscript for important intellectual content. All authors reviewed, edited, and approved the final version of the manuscript, authorized its submission for publication, and agree to be accountable for all aspects of the work.
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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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".