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Brand-specific estimates of influenza vaccine effectiveness for the 2021–2022 season in Europe

Results from the DRIVE multi-stakeholder study platform

Bibliographic Data

ID22079133
AuthorsAnke L Stuurman (0000-0002-4157-1315), Antonio Losa Carmona (0000-0002-1366-1671, Instituto de Salud Carlos III, corresponding author), Antonio Carmona, Jorne Biccler, Jorne Lionel Biccler (0000-0002-8180-3782), A Descamps (0000-0003-2437-7876, Inserm), Miriam Levi (0000-0002-0086-3952, Azienda Usl Toscana Centro), Ulrike Baum (0000-0002-7456-8016, Finnish Institute for Health and Welfare), Ainara Mira‐Iglesias (0000-0001-6371-8229, Instituto de Salud Carlos III), Ainara Mira-Iglesias, Stefania Bellino (0000-0003-1149-3835, Istituto Superiore di Sanità), Uy Hoang (0000-0002-8428-5140, University of Oxford), Simon De Lusignan (0000-0002-8553-2641, University of Oxford), Roberto Bonaiuti (0000-0001-9644-499X, University of Florence), Bruno Lina (0000-0002-8959-2123, Lyon 1 Université), Caterina Rizzo (0000-0002-5583-7508, University of Pisa), Hanna Nohynek (0000-0001-8220-3669, Finnish Institute for Health and Welfare), Javier Díez‐Domingo (0000-0003-1008-3922, Instituto de Salud Carlos III), Javier Díez-Domingo, DRIVE Study Contributors
Year2023
Volume11
Pages1195409-1195409
Publication date2023-07-20
Open AccessYes
TypeARTICLE
VenueFrontiers in Public Health (JOURNAL)
Journal identifiersISSN: 2296-2565 • E-ISSN: 2296-2565
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2023.1195409
PMID37546295
OpenAlexW4385065869
LanguageEN
References cited18

Introduction: Development of Robust and Innovative Vaccine Effectiveness (DRIVE) was a European public-private partnership (PPP) that aimed to provide annual, brand-specific estimates of influenza vaccine effectiveness (IVE) for regulatory and public health purposes. DRIVE was launched in 2017 under the umbrella of the Innovative Medicines Initiative (IMI) and conducted IVE studies from its pilot season in 2017-2018 to its final season in 2021-2022. Methods: In 2021-2022, DRIVE conducted four primary care-based test-negative design (TND) studies (Austria, Italy, Iceland, and England; involving >1,000 general practitioners), nine hospital-based TND studies (France, Iceland, Italy, Romania, and Spain, for a total of 21 hospitals), and one population-based cohort study in Finland. In the TND studies, patients with influenza-like illness (primary care) or severe acute respiratory infection (hospital) were enrolled, and laboratory tested for influenza using RT-PCR. Study contributor-specific IVE was calculated using logistic regression, adjusting for age, sex, and calendar time, and pooled by meta-analysis. Results: In 2021-2022, pooled confounder-adjusted influenza vaccine effectiveness (IVE) estimates against laboratory-confirmed influenza (LCI) overall and per type and subtype/lineage was produced, albeit with wide confidence intervals (CI). The limited circulation of influenza in Europe did not allow the network to reach the optimal sample size to produce precise IVE estimates for all the brands included. The most significant IVE estimates were 76% (95% CI 23%-93%) for any vaccine and 81% (22%-95%) for Vaxigrip Tetra in adults ≥65 years old and 64% (25%-83%) for Fluenz Tetra in children (TND primary care setting), 85% (12%-97%) for any vaccine in adults 18-64 years (TND hospital setting), and 38% (1%-62%) in children 6 months-6 years (population-based cohort, mixed setting). Discussion: Over five seasons, DRIVE collected data on >35,000 patients, more than 60 variables, and 13 influenza vaccines. DRIVE demonstrated that estimating brand-specific IVE across Europe is possible, but achieving sufficient sample size to obtain precise estimates for all relevant stratifications remains a challenge. Finally, DRIVE's network of study contributors and lessons learned have greatly contributed to the development of the COVID-19 vaccine effectiveness platform COVIDRIVE

Cohort · Confidence interval · Environmental health · Family medicine · Influenza vaccine · Logistic regression · Population · Public health · Vaccination · Demography · Influenza Virus Research Studies · Medicine · Nursing · Respiratory viral infections research · Vaccine Coverage and Hesitancy · Immunology · Internal Medicine

  • A basic introduction to fixed-effect and random-effects models for meta-analysis

    Open Access•Michael Borenstein, Larry V Hedges et al.•Research Synthesis Methods•2010

  • Challenges and Adaptation of a European Influenza Vaccine Effectiveness Study Platform in Response to the Covid-19 Emergence

    Open Access•Antonio Losa Carmona, Antonio Carmona et al.•International Journal of…•2021

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