Brand-specific estimates of influenza vaccine effectiveness for the 2021-2022 season in Europe : results from the DRIVE multi-stakeholder study platform
Copyright © 2023 Stuurman, Carmona, Biccler, Descamps, Levi, Baum, Mira-Iglesias, Bellino, Hoang, Lusignan, Bonaiuti, Lina, Rizzo, Nohynek, Díez-Domingo and DRIVE Study Contributors..
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.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:11 |
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| Enthalten in: |
Frontiers in public health - 11(2023) vom: 04., Seite 1195409 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Stuurman, Anke L [VerfasserIn] |
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| Links: |
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| Anmerkungen: |
Date Completed 08.08.2023 Date Revised 08.08.2023 published: Electronic-eCollection Citation Status MEDLINE |
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| doi: |
10.3389/fpubh.2023.1195409 |
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| Förderinstitution / Projekttitel: |
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NLM360459684 |
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| 245 | 1 | 0 | |a Brand-specific estimates of influenza vaccine effectiveness for the 2021-2022 season in Europe |b results from the DRIVE multi-stakeholder study platform |
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| 500 | |a Date Revised 08.08.2023 | ||
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| 500 | |a Citation Status MEDLINE | ||
| 520 | |a Copyright © 2023 Stuurman, Carmona, Biccler, Descamps, Levi, Baum, Mira-Iglesias, Bellino, Hoang, Lusignan, Bonaiuti, Lina, Rizzo, Nohynek, Díez-Domingo and DRIVE Study Contributors. | ||
| 520 | |a 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 | ||
| 520 | |a 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 | ||
| 520 | |a 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) | ||
| 520 | |a 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 | ||
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| 650 | 4 | |a test-negative design | |
| 650 | 4 | |a vaccine effectiveness | |
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| 650 | 7 | |a Influenza Vaccines |2 NLM | |
| 700 | 1 | |a Carmona, Antonio |e verfasserin |4 aut | |
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| 700 | 1 | |a Levi, Miriam |e verfasserin |4 aut | |
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| 700 | 1 | |a Rizzo, Caterina |e verfasserin |4 aut | |
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| 700 | 1 | |a Díez-Domingo, Javier |e verfasserin |4 aut | |
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| 700 | 1 | |a Streinu-Cercel, Anca |e investigator |4 oth | |
| 700 | 1 | |a Bilaşco, Anuţa |e investigator |4 oth | |
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| 700 | 1 | |a Rodríguez, Isabel Gil |e investigator |4 oth | |
| 700 | 1 | |a Alvarez, Antonio Muro |e investigator |4 oth | |
| 700 | 1 | |a Garcia, Moncef Belhassen |e investigator |4 oth | |
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| 700 | 1 | |a Panatto, Donatella |e investigator |4 oth | |
| 700 | 1 | |a Montomoli, Emanuele |e investigator |4 oth | |
| 700 | 1 | |a Castaldi, Silvana |e investigator |4 oth | |
| 700 | 1 | |a Orsi, Andrea |e investigator |4 oth | |
| 700 | 1 | |a Domnich, Alexander |e investigator |4 oth | |
| 700 | 1 | |a Chironna, Maria |e investigator |4 oth | |
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| 700 | 1 | |a Manini, Ilaria |e investigator |4 oth | |
| 700 | 1 | |a Napoli, Christian |e investigator |4 oth | |
| 700 | 1 | |a Torsello, Alessandra |e investigator |4 oth | |
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| 700 | 1 | |a Pagarolas, Andrés Antón |e investigator |4 oth | |
| 700 | 1 | |a Andrés, Cristina |e investigator |4 oth | |
| 700 | 1 | |a Carbonés, Ingrid |e investigator |4 oth | |
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| 700 | 1 | |a Orrico-Sánchez, Alejandro |e investigator |4 oth | |
| 700 | 1 | |a López-Labrador, F Xavier |e investigator |4 oth | |
| 700 | 1 | |a Mengual-Chuliá, Beatriz |e investigator |4 oth | |
| 700 | 1 | |a Soler, Judit Sánchez |e investigator |4 oth | |
| 700 | 1 | |a Palomino, María Jinglei Casanova |e investigator |4 oth | |
| 700 | 1 | |a Mollar-Maseres, Juan |e investigator |4 oth | |
| 700 | 1 | |a Tortajada-Girbés, Miguel |e investigator |4 oth | |
| 700 | 1 | |a Rodríguez-Blanco, Noelia |e investigator |4 oth | |
| 700 | 1 | |a Carballido-Fernández, Mario |e investigator |4 oth | |
| 700 | 1 | |a Ivorra, Raquel Andreu |e investigator |4 oth | |
| 700 | 1 | |a Fortuny, Àngels Sierra |e investigator |4 oth | |
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| 700 | 1 | |a Ureta, Cristina Mingot |e investigator |4 oth | |
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| 700 | 1 | |a Pla, Ángela Sánchez |e investigator |4 oth | |
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| 700 | 1 | |a Alberola, Juan |e investigator |4 oth | |
| 700 | 1 | |a Nogueira, José Miguel |e investigator |4 oth | |
| 700 | 1 | |a Camarena, Juan J |e investigator |4 oth | |
| 700 | 1 | |a Arjona-Zaragozí, Francisco |e investigator |4 oth | |
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| 700 | 1 | |a López-Hontangas, José Luis |e investigator |4 oth | |
| 700 | 1 | |a Gómez, María Dolores |e investigator |4 oth | |
| 700 | 1 | |a Martín-Quirós, Alejandro |e investigator |4 oth | |
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| 700 | 1 | |a Cendejas, Emilio |e investigator |4 oth | |
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| 700 | 1 | |a Vannacci, Alfredo |e investigator |4 oth | |
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