Real-World Effectiveness of Live Attenuated vs. Inactivated Influenza Vaccines in Children
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,007 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,002 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».