# Influenza vaccine effectiveness and genetic diversity: insights from end-of-season community surveillance, France, 2024-2025

Allan de Clercq, François Blanquart, Vincent Vieillefond, Benoit Visseaux, Claire Nour, Abou Chakra, Marta C Nunes, Alexandra Jacques, Stéphanie Haim-Boukobza, Valentin Wehrle, et al.

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Allan de Clercq, François Blanquart, Vincent Vieillefond, Benoit Visseaux, Claire Nour, et al. "Influenza vaccine effectiveness and genetic diversity: insights from end-of-season community surveillance, France, 2024-2025. Emerging microbes & infections, inPress, 10.1080/22221751.2025.2562045. pasteur-05262553

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# Influenza vaccine effectiveness and genetic diversity: insights from end-of-season community surveillance, France, 2024-2025

Allan De Clercq, François Blanquart, Vincent Vieillefond, Benoit Visseaux, Claire Nour Abou Chakra, Marta C Nunes, Alexandra Jacques, Stéphanie Haim-Boukobza, Valentin Wehrle, Guillaume Deleglise, Thomas Duret, Sibylle Bernard-Stoecklin, Danielle Perez Bercoff, Bruno Lina, Marie Anne Rameix-Welti, Laurence Josset, Vincent Enouf, on behalf of the RELAB study group & Antonin Bal

**To cite this article:** Allan De Clercq, François Blanquart, Vincent Vieillefond, Benoit Visseaux, Claire Nour Abou Chakra, Marta C Nunes, Alexandra Jacques, Stéphanie Haim-Boukobza, Valentin Wehrle, Guillaume Deleglise, Thomas Duret, Sibylle Bernard-Stoecklin, Danielle Perez Bercoff, Bruno Lina, Marie Anne Rameix-Welti, Laurence Josset, Vincent Enouf, on behalf of the RELAB study group & Antonin Bal (15 Sep 2025): Influenza vaccine effectiveness and genetic diversity: insights from end-of-season community surveillance, France, 2024-2025, Emerging Microbes & Infections, DOI: 10.1080/22221751.2025.2562045

**To link to this article:** https://doi.org/10.1080/22221751.2025.2562045

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© 2025 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group, on behalf of Shanghai Shangyixun Cultural Communication Co., Ltd

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**Publisher:** Taylor & Francis & The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group, on behalf of Shanghai Shangyixun Cultural Communication Co., Ltd

**Journal:** Emerging Microbes & Infections

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# Influenza vaccine effectiveness and genetic diversity: insights from end-of-season community surveillance, France, 2024-2025

**Authors:** Allan De Clercq¹, François Blanquart², Vincent Vieillefond³, Benoit Visseaux⁴, Claire Nour Abou Chakra⁵, Marta C Nunes⁵,⁶, Alexandra Jacques⁷, Stéphanie Haim-Boukobza⁸, Valentin Wehrle⁹, Guillaume Deleglise¹⁰, Thomas Duret¹⁰, Sibylle Bernard-Stoecklin¹¹, Danielle Perez Bercoff¹², Bruno Lina¹,¹³, Marie Anne Rameix-Welti¹²,¹⁴, Laurence Josset¹,¹³, Vincent Enouf¹², on behalf of the RELAB study group¹⁵, Antonin Bal¹,¹³,✉

## Affiliations

1. Hospices Civils de Lyon (HCL), Centre National de Référence des virus des infections respiratoires, Institut des Agents Infectieux, Laboratoire de Virologie, Lyon, France.

2. Center for Interdisciplinary Research in Biology (CIRB), Collège de France, CNRS, INSERM, PSL Research University, Paris, France.

3. BPO-BIOEPINE-Biogroup, Levallois-Perret, France

4. Département d'infectiologie, Laboratoire Cerba, Cerba Healthcare, Frépillon, France

5. Center of Excellence in Respiratory Pathogens (CERP), Hospices Civils de Lyon (HCL), Lyon, France; Centre International de Recherche en Infectiologie (CIRI), Équipe Santé Publique, Épidémiologie et Écologie Évolutive des Maladies Infectieuses (PHE3ID), Inserm U1111, CNRS UMR5308, ENS de Lyon, Université Claude Bernard Lyon 1, Lyon, France.

6. South African Medical Research Council, Vaccines & Infectious Diseases Analytics Research Unit, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa

7. Biogroup Lorraine, Grand Est

8. Laboratoires Cerballiance, Cerba Healthcare, Issy-les-Moulineaux, France

9. BioLBS, 3 Place Félix Faure, 76170 Lillebonne, France

10. INOVIE GEN-BIO, 8 rue Jacqueline Auriol, 63100 Clermont-Ferrand, France

11. Santé Publique France – Direction des maladies infectieuses, Saint-Maurice, France

12. National Reference Center for Respiratory Viruses, Molecular Mechanisms of Multiplication of Pneumovirus, Institut Pasteur, Université Paris Cité, Paris, France
13. Centre International de Recherche en Infectiologie (CIRI), Laboratoire VirPath, Inserm U1111, CNRS UMR5308, ENS de Lyon, Université Claude Bernard Lyon 1, Lyon, France

14. Molecular Mechanisms of Multiplication of Pneumovirus, Université Versailles St-Quentin en Yvelines, Paris-Saclay INSERM UMR 1173 (2I), Assistance Publique des Hôpitaux de Paris, Paris, France

15. Members of the RELAB study group are acknowledged at the end of the article

**Correspondence:** ✉ Antonin Bal
Associate Professor
Hospices Civils de Lyon
National reference center for respiratory viruses
Grande-Rue de la Croix Rousse
69317, Lyon, France
Phone: +33 4 72 07 11 11
Email: antonin.bal@chu-lyon.fr

**Collaborative group:** Members of the RELAB Study Group : Valentin Wehrle (bioLBS), Guillaume Deleglise (INOVIE), Thomas Duret (INOVIE) Arnaud François (Bioesterel, Biogroup PACA); Alexandre Vignola (Oriade Noviale, Biogroup AURA); Vincent Garcia (Alphabio, Biogroup PACA); Alexandra Jacques (Biogroup Lorraine, Grand Est); Jonas Amzalag (Biolam, Biogroup IDF); Nadège Gourgouillon (CAB Biogroup, Grand Est); Remi Labetoulle (Laborizon, Biogroup Nouvelle Aquitaine); Frederique Roumanet (Unilians, Biogroup AURA); Arthur Denoel (Laborizon, Biogroup Bretagne); Hilel Mehamha (CBM25, Biogroup Bourgogne Franche-Comté); Thierry Guffond (Diagnovie, Biogroup Hauts de France); Magali HYPOLITE (2A2B, Biogroup Corse); Yanis Chaib (Biolam, Biogroup IDF); Timothée Goetschy (Biogroup national, équipe Data); Elodie Ostermann (Biogroup national, équipe Data); Anne Holstein (Laborizon Biogroup Centre Val de Loire); Vincent Vieillefond (BPO-Bioépine Biogroup IDF); Jean Marc Giannoli (Biogroup national); Julienne de Pontcharra (Bioesterel, Biogroup PACA); Jean Francois Comes (Laborizon, Biogroup Bretagne); Justine Gasnot (Bioesterel, Biogroup PACA); Theo Corbet (Unilians, Biogroup AURA); Laurent Kbaier (Bioesterel, Biogroup PACA); Emmanuel Chanard (Cerballiance, Auvergne Rhône Alpes); Arcadie Gioud (Cerba Xpert, Auvergne Rhône Alpes); Stéphanie Arsene (Cerballiance, Normandie Bocage); Maxime Sansot (Cerballiance, Pays de Loire); Anne-Lise Gautier (Cerballiance, Portes de Bretagne); Kariach Goldar (Cerballiance, Martinique); Mahery Ramiandrisoa (Cerballiance, Réunion); Aristide Nzeumi (Cerballiance, Réunion); Pauline Jestin (Cerballiance, Charentes); Gilles Abs (Cerballiance, Centre Val-de-Loire); Guillemette Wandler (Cerballiance, Centre Valde-Loire); Anne-Claire Strzelecki (Cerballiance,
Occitanie); Sarah Cerdan (Cerballiance, Occitanie); Edouard Delaunay (Cerballiance, Alpes Durance); Sandrine Barrieu-Moussat (Cerballiance, Côte d'azur); Laurence Prots (Cerballiance, Côte d'azur); Edouard Delaunay (Cerballiance, Provence); Johanna Roux (Cerballiance, Ile-de-France Est); Yasmina De Saint Salvy (Cerballiance, Ile-de-France Est); Agnes Durand (Cerballiance, Ile-de-France Est); Aude Lesenne (Cerballiance, Ile-de-France Sud); Kader Merah (Cerballiance, Ile-de-France Sud); Erwan Le Naour (Cerballiance, Aquitaine Nord); David Robert (Cerballiance, Aquitaine Nord); Sophie Zaffreya (Cerballiance, Aquitaine Nord); Jean-Philippe Galhaud (Cerballiance, Aquitaine Sud); Claire Felloni (Cerballiance, Artois); Dominique Dyda (Cerballiance, Haut-de-France); Aurelie Dupuis (Cerballiance, Bretagne); Gwenole Prigent (Cerballiance, Bretagne); Stephanie Arsene (Cerballiance, Normandie Ouest); Antoine Prigent (Cerballiance, Normandie Ouest); Natacha Tatoyan (Cerballiance, Nouvelle Calédonie); Benoit Visseaux (Laboratoire Cerba, Pole Infectiologie); Bénédicte Roquebert (Laboratoire Cerba, Pole Infectiologie); Stéphanie Haim-Boukobza (Cerba Healthcare); Odile Rousselet (Cerba Healthcare) and Michel Sala (Cerba Healthcare).

## Abstract

Influenza 2024-2025 season in France was characterized by prolonged duration, unusual co-circulation of all three viruses (A(H1N1)pdm09, A(H3N2), B/Victoria) with several subclades, and substantial healthcare impact. We aimed to investigate the impact of influenza genetic diversity on vaccine effectiveness (VE).

A test-negative design study was conducted to estimate VE in a large cohort from the RELAB network of community-based laboratories (n = 77,704 patients). A subset of sequenced samples (n = 2,119 patients) allowed VE estimation for several clades and subclades as well as comparison of subclade distribution by vaccination status.

Vaccine coverage was 45% in patients aged 65 years and older (65+). VE based on PCR-confirmed infections was 44% (95% CI: 41-48%) and lower in 65+ individuals, at 25% (95% CI:18-31%) especially for type A virus (23%; 95% CI: 13-32%) compared to type B virus (57%; 95% CI: 35-72%). Sequencing-confirmed VE among individuals vaccinated 15 days to 3 months prior testing, was 41% (95% CI: 14-60%) for A(H1N1)pdm09 and 47% (95% CI: 21-64%) for its main subclade 5a.2a(C.1.9.3); A(H3N2) estimate was 30% (95% CI:5-48%) and 31% (95% CI:4-50%) for 2a.3a.1(J.2) subclade. The emerging A(H1N1)pdm09 5a.2a.1 (D.3) subclade was significantly more frequent among vaccinated individuals compared to unvaccinated.
The low vaccine coverage combined with the notably low effectiveness against A(H3N2) and for type A in elderly may have contributed to the high influenza activity this season. The emergence of A(H1N1)pdm09 5a.2a.1 (D.3) raises uncertainty and requires surveillance.

**Keywords:** Influenza, vaccine effectiveness, acute respiratory infection, surveillance, community testing

**Introduction**

Epidemiological surveillance across European countries during the 2024-2025 influenza season reported co-circulation of three influenza viruses: subtypes A(H1N1)pdm09, A(H3N2), and B/Victoria lineage [1-4]. Aggregated weekly test positivity from the ILI/ARI virological surveillance conducted in primary care networks across 23 European countries peaked in week 5 of 2025, reaching 48%, the highest level recorded since the system was established in the 2021-2022 season [1].

In France, the epidemic season started in early December (week 49) and ended in late February (week 8), lasting 10 weeks, longer than the average duration observed in the 2011-2024 seasons [5]. The vaccination campaign ran from October 15, 2024 to February 28, 2025, using only the quadrivalent standard dose inactivated vaccine. Vaccination was recommended for individuals aged 65 years and older (65+), patients aged over 6 months with chronic conditions or obesity, pregnant women, and residents in rehabilitation or medico-social care facilities. The composition of the vaccine for the northern hemisphere 2024/25 includes strains 5a.2a.1 for A(H1N1)pdm09, which remained unchanged from the previous season, 2a.3a.1 for A(H3N2), and V1A.3a.2 for B/Victoria viruses [6].

France experienced an excess in all-cause mortality, particularly high during the epidemic peak (weeks 01-02/2025) in hospitals and medico-social facilities, with an estimated 14,100 excess deaths over the season [5,7]. The severity of influenza infection during 2024-2025 could be associated with several factors including the co-circulation of different influenza types and subtypes, low vaccine coverage and low VE for the circulating strains.

In France, VE against influenza infection in the community can be readily assessed in real time using the RELAB network launched during the 2023-2024 season [8].

VE using the RELAB network was first estimated during the previous season (2023-2024), with an overall VE of 48% (95% CI: 44%-51%). During the 2024-2025 season, interim VE by types and subtypes were assessed, while VE by genetic subclade has not yet been evaluated.

This end-of-season report consolidates interim estimates [9] of influenza VE from a large population and provides insights into VE with a finer genomic resolution.
# Methods

## Study population

RELAB is a network of private community-based laboratories with 1,600 locations nationwide. This season, the participating laboratories included BIOGROUP, CERBALLIANCE, INOVIE GEN-BIO, and BioLBS.

As for the previous season, samples from the RELAB-associated laboratories underwent triplex RT-PCR testing and were linked with virological and clinical information transmitted to national references centres for viral respiratory infections (NRC-VIR) at the Hospices Civils de Lyon and the Institut Pasteur Paris [10]. Additionally, a random subset of positive samples was submitted for genomic sequencing by NRC-VIR.

## Inclusion criteria

The clinical information retained for the VE analysis was sex, age-group, PCR technique, week of testing, vaccination between 15 days and 6 months prior testing (15d-6m) or unvaccinated. Within the 15d-6m vaccinated group, two subcategories were defined: individuals vaccinated between 15 days and 3 months prior to testing (15d-3m), and those between 3 and 6 months (3m-6m). Tests conducted in French overseas departments (n = 3,490), those with missing clinical information (n = 79,924), and repeated tests for same individuals (n = 2,180) were excluded from the analysis. As for the interim analysis [9], self-reported 3m-6m vaccinations before mid-January were excluded from the analysis due to implausible timing (n = 313). The study population of the VE analysis included patients with a RT-PCR test collected from week 44 of 2024 to week 14 of 2025 (28/10/2024 to 31/03/2025) who met the inclusion criteria.

For the analysis of vaccination distribution among influenza subclades, the collection period of RT-PCR tests was expanded from week 42 of 2024 to week 22 of 2025 (14/10/2024 to 01/06/2025) to strengthen the analysis and pursue the surveillance of the emerging subclades. The analysis restricted to individuals either vaccinated within 15d-6m or unvaccinated.

## Statistical analyses

Statistical analyses were performed with R version 4.3.2 [11]. Categorical variables were described by counts and proportions, and comparisons between groups were performed using Pearson's chi-squared test.
As previously detailed in the interim analysis [9], a test-negative design was used to estimate VE and was measured as (1 - OR) with 95% confidence intervals (CIs), where OR represents the odds ratio of vaccination among test-positive to the odds ratio of vaccination among test-negatives. We fitted a logistic regression model (generalized linear model with binomial response), adjusted on sex, age-group, PCR technique, week of testing (as a categorical variable) and vaccination status. Covariates were selected based on the Akaike information criterion. Stratified analysis by age-group were performed without that variable.

Analyses of vaccination distribution across influenza subclades were conducted using Pearson's chi-squared test, with Bonferroni adjustment applied for multiple comparisons.

# Results

## Influenza infection in community

Overall, 77,704 patients met the inclusion criteria of the VE analysis (complete metadata, weeks 44-14, and vaccination within 15 days to 6 months prior to testing, or unvaccinated) including test-positive (n = 20,650; 27%) and test-negative individuals (n = 57,054; 73%) [Table 1]. Among the positive individuals, the majority were aged 18-64 years (n = 11,996; 58%). Of the PCR-positive samples that underwent typing (n = 12,295; 60%), influenza A was more frequently detected (n = 7,967; 65%) than influenza B (n = 4,272; 35%).

Test positivity reached 49% (n = 2,379/4,840) for unvaccinated individuals on week 4/2025 and 25% (n = 213/858) on week 1/2025 for vaccinated individuals [Figure 1A]. Influenza A positivity for unvaccinated and vaccinated individuals both also reached on week 4/2025 with respectively, 27% (n = 909/2,461) and 15% (n = 133/863) [Figure 1B]. Influenza B activity reached the highest positivity on week 6 with 18% (502/2,802) for unvaccinated individuals, while positivity in vaccinated remained very low with 3% (20/700) [Figure 1C].

Among the different age categories, those aged 65 years and older (65+) recorded the highest proportion of influenza A positive tests across the season [Figure 2]. Meanwhile, the 0-4, 5-17, and 18-64 age groups followed a comparable pattern, with influenza A predominating initially but declining over the course of the season, as influenza B became more prevalent. Vaccine coverage among individuals aged 65+ was 45% (n = 7,937/17,487) [Table 2].

## Influenza genetic diversity
A random subset of 4,612 influenza-positive samples from the RELAB Network was sequenced between week 42/2024 and week 22/2025. Among the 4,448 samples collected between weeks 44/2024 and 14/2025, the most frequently sequenced virus was B/Victoria (1,634/4,448; 37%), followed by A(H3N2) (1,426/4,448; 32%) and A(H1N1)pdm09 (1,388/4,448; 31%) [Supplementary Figure S1].

Within the lineage B/Victoria, the only clade identified was V1A.3a.2 with three major sub-clades [Figure 3AB, Supplementary Figure 1C]. The clade 2a.3a.1 was dominant among H3N2 viruses (n = 1,424/1,426; 100%) with 2a.3a.1(J.2) (n = 1,197/1,426; 84%), representing the most prevalent subclade of the season [Figure 3CD, Supplementary Figure 1C]. Among A(H1N1)pdm09 viruses, the main clades identified were 5a.2a (n = 1,263/1,388; 91%) and 5a.2a.1 (n = 125/1,388; 9%) [Figure 3EF, Supplementary Figure 1C]. The dominant subclade was 5a.2a.1(C.1.9.3) (n = 958/1,388; 69%), with 5a.2a.1(D.3) subclade emerging around week 50 and sharply increasing in proportion to become the most prevalent.

Of these sequenced samples, 2,119 met the inclusion criteria for the VE analysis (complete metadata, weeks 44–14, and vaccination within 15 days to 6 months prior to testing, or unvaccinated) [Supplementary Table 1]

## Vaccine effectiveness against RT-PCR confirmed influenza infection

We estimated the evolution of the VE during the season for the individuals vaccinated within 15d-6m [Figure 4A, Supplementary Table 2]. Overall VE from late December 2024, early February 2025 (interim), to the end-of-season showed very similar point estimates (45%, 43%, 45%, respectively) with small CIs and increasing precision as the study population grew. Similar findings were observed when restricting to B viruses (81%, 79% and 78%, respectively), while influenza A VE declined slightly over the season, although with overlapping CIs [41% (95% CI:27-52%), 31% (95% CI:24-38%), and 32% (95% CI:27-37%), respectively]. End-of-season VE for influenza A decreased significantly by 17% when comparing individuals aged 0–64 years (40%, 95% CI:33-46%) to those aged 65+ (23%, 95% CI:13-32%).

When separating the vaccination categories 15d-3m and 3m-6m VE similar results were obtained for overall and in influenza B (2% difference in point estimates with overlapping CIs) [Figure 4BC, Supplementary Table 3]. Influenza A VE waned by 6%, although the CIs overlapped.

## Vaccine effectiveness by subtypes, clades and subclades
The end-of-season VE based on sequencing-confirmed influenza cases of the 15d-3m category against influenza B and A were 84% (95% CI: 69-92%) and 35% (95% CI: 19-48%), i.e. similar to the PCR-confirmed VE estimates [Figure 5A, Supplementary Table 3]. Among influenza A subtypes, VE against A(H3N2) was 30% (95% CI: 5-48%) and against A(H1N1)pdm09 was 41% (95% CI: 17-57%). Assessing VE for clades and subclades with sufficient sub-population size, VE against A(H1N1)pdm09 5a.2a was 41% (95% CI: 14-60%), and against the specific subclade C.1.9.3 was 47% (95% CI: 21-64%). VE estimates for A(H3N2) and its clade 3a.1 were equivalent, as it was the only clade detected; VE against infection with A(H3N2) major subclade, J.2, was 31% (95% CI: 5% to 50%). No significant differences in VE against infection with the subclades of B/Victoria were observed.

As for 3m-6m VE, Influenza B estimates remained constant, although no significant results were observed for influenza A, as their CIs overlapped 0, likely due to the reduced number of sequences and decreased A(H1N1)pdm09 activity late in the season (see Discussion) [Figure 5B, Supplementary Table 3].

### Distribution of vaccination among influenza subclades

We examined the distribution of subclades by vaccination status (15d-6m) during weeks 42/2024 to 22/2025 (n = 2,299) [Figure 6]. As expected, due to its low VE, subclade J.2 within A(H3N2) viruses was significantly more frequent among vaccinated individuals (n = 103/222; 46%) than unvaccinated (n = 511/2,077; 25%) (Pearson's chi-squared test, Bonferroni-adjusted p < 0.01) [Supplementary Table 4]. Subclade D.3 A(H1N1)pdm09 was also more frequent among vaccinated individuals (n = 12/222; 6%) than unvaccinated (n = 32/2,077; 2%). In contrast, Type B subclades C.5.1, C.5.6, and C.5.7 were more frequent among unvaccinated individuals.

> **No significant differences in the prevalence of substitutions were observed between vaccinated and unvaccinated individuals across clades and subclades (Pearson's chi-squared test, Bonferroni-adjusted p-values > 0.05)."** Discussion

The vaccination campaign in France began on October 15, 2024, only 1 month before the start of the influenza season (week 46) and was extended until February 28, 2025. The quadrivalent standard dose inactivated vaccine was the only one available in France this season.

Temporal comparison of VE indicates that the RELAB network covers a sufficiently large population to produce robust VE estimates as early as late December. End-of-season results were consistent with European interim estimates [12], which reflect a combination of inactivated, high-dose and adjuvanted
vaccine. In contrast, Canadian interim estimates [13] showed higher effectiveness, particularly among individuals aged 65+, which may reflect the administration of high-dose or adjuvanted vaccines, as shown to improve protection in older adults [14].

Type A estimates VE based on sequencing-confirmed influenza cases vaccinated within 3m-6m wane to non-significance with CIs including 0 (p-value > 0.05). However, PCR-confirmed type A VE did not show clear evidence of waning (6% with overlapping CIs) and may reflect changes in circulating strains rather than a true decline in effectiveness. A plausible explanation for sequencing-confirmed waning 3m-6m involves methodological artefacts affecting the limited sample size of A(H1N1)pdm09 estimates, including the depletion-of-susceptibles bias [15] and the “leaky” vaccine effect [16]. The distribution of subclade D.3 may also have contributed to the lower VE estimates.

Last season, overall VE was estimated at 48% (95% CI: 44%-51%) [10]. Stratified by age group, the overall VE was lower among individuals aged 65+ at 42% (95% CI: 37-47%), compared those age 0-64 years at 53% (95% CI: 49%-57%). VE against infection by influenza A was 47% (95% CI: 41-52%), while no estimates for type B and types stratified by age-group were performed. Among the sequenced viruses, A(H1N1)pdm09 accounted for 72% (mainly 5a.2a clade) and A(H3N2) for 27% (mainly 2a.2a clade) with negligible circulation of B/Victoria viruses. VE against influenza A subtypes infections was estimated at 38% (95% CI: 20-52%) for A(H1N1)pdm09 and 41% (95% CI: 8-63%) for A(H3N2).

Compared to the previous season results in the same population [10], the vaccine coverage within 15d-6m increased by 3% (42% to 45%). These rates remain insufficient for the 75% World Health Organization target [17]. Overall VE for 15d-6m vaccination interval declined (48% to 45%) and particularly in individuals aged 65+ with 17 points of reduction (42% to 25%). Influenza A VE waned by 15 points (47% to 32%) including a reduction of 12 points for A(H3N2) (41% to 29%). Unlike A(H3N2), the composition of the A(H1N1)pdm09 vaccine remains unchanged and the VE suggests no attenuation (41% to 40% for 15d-3m vaccination) over the two consecutive seasons. Antigenic characterization supports these findings with A(H1N1)pdm09 viruses remaining antigenically similar to the vaccine strain, unlike A(H3N2), which showed partial mismatch [5].

In the present study, the frequency of the subclade A(H1N1)pdm09 D.3 within the 5a.2a.1 vaccine clade for the Southern Hemisphere 2024/25, Northern Hemisphere 2024/25, and Southern Hemisphere 2025/26 seasons [18] increased at the very end of the season and was observed more frequently among vaccinated individuals. Due to the limited sample size, VE against D.3 subclade was not computed. No difference in substitutions on the HA segment were observed in D.3 infections between vaccinated
and unvaccinated individuals. Further investigation is needed to assess whether this reflects a true
difference in fitness, immune evasion, or a confounding factor. Subclade D.3 emerged as the dominant
A(H1N1)pdm09 variant worldwide by April 2025 and is currently the most prevalent in Australia at
the start of their influenza season [19].

When examining the substitutions present in the HA segment, we observed that all cases, both vaccinated and unvaccinated individuals, infected with subclade D.3 viruses carried the HA1:T120A mutation. This substitution also defines subclade C.1.9, consequently, every virus belonging to subclade C.1.9.3, the most predominant A(H1N1)pdm09 virus during the season, also harbored the HA1:T120A mutation. Notably, this mutation is absent from the A(H1N1)pdm09 vaccine strain included in the 2024–25 Northern Hemisphere formulation, A/Victoria/4897/2022 [18].

For subclade J.2 of A(H3N2), which was the most prevalent A(H3N2) subclade during the season and associated with lower estimated vaccine effectiveness, we observed the HA1:N122D mutation in all cases (vaccinated and unvaccinated). This substitution results in the loss of an N-linked glycosylation site [20] and may have contributed to the reduced vaccine effectiveness observed for A(H3N2) this season. In addition, the HA1:N8D mutation, also linked to the loss of an N-linked glycosylation site [21], was detected in 65% of vaccinated cases and 61% of unvaccinated cases. Both HA1:N122D and HA1:N8D were absent from the A(H3N2) vaccine strain included in the 2024–25 Northern Hemisphere formulation, A/Thailand/8/2022 [18]. The HA1:N122D mutation has since been incorporated into the 2025 Southern Hemisphere vaccine formulation [22] and the 2025–2026 Northern Hemisphere vaccine formulation [23].

Our results underscore the value of large-scale genomic surveillance in contributing to vaccine strain selection for the upcoming season. Our preliminary results on the recently emerging D.3 variant should be further investigated using hemagglutination inhibition assays. Combined with epidemiological data from Australia, our findings suggest that this strain might be considered in future vaccine development. Looking ahead, the main challenge for the RELAB network will be to support integrative approaches that combine vaccination status and phylogenetic analysis to better characterize vaccine immune escape variants.

As in the interim analysis, we used the same methodology and are therefore subject to the same limitations: selection bias (test-seeking behaviour), confounding by health status ('healthy vaccine bias' and 'confounding by indication'), recall bias (self-reported vaccination) and the difficulty to derive the implications of our findings regarding more severe infections, e.g. hospitalisation and mortality rates [9].
**Conclusion**

The low vaccine coverage combined with the notably low effectiveness against A(H3N2) and for type A in elderly may have contributed to the high influenza activity this season. The emergence of A(H1N1)pdm09 5a.2a.1 (D.3) raises uncertainty and requires surveillance. The upcoming introduction of the high-dose and adjuvanted influenza vaccine in France next season [24] could improve VE and will require further genomic-based assessment to evaluate its impact on circulating variants.

**Acknowledgments**

We would like to acknowledge all members of RELAB laboratories.

**Authors' contributions**

AD, FB performed statistical analyses and drafted the manuscript. AB conceptualised the study, supervised data collection, provided feedback on analyses and drafted the manuscript. VV, BV, AJ, SHB, VW, GD, TD, SBS, DTB, BL, MARW, LJ, VE supervised data collection within community laboratories, participated to the study conceptualisation and implementation. MCN and CNABC contributed in methodological expertise and analyses. All authors contributed to the interpretation of the results, commenting and critical revision of the manuscript, and approved the final version for submission.

**Disclosure statement**

No potential conflict of interest was reported by the author(s)

**Ethical statement**

The study protocol received approval from the institutional review board of the Hospices Civils de Lyon (Comité Scientifique et Éthique des Hospices Civils de Lyon) in June 2023 (reference 23-5039). All patients or the parents of minors were provided with an information notice explaining the nature and purpose of the collected data. In cases where a patient or parent objected to data usage, the corresponding data was excluded from the research database. To ensure confidentiality, unique anonymized alphanumeric identifiers were assigned, and data transfers to the research team were conducted via a secure portal, accessible exclusively to authorized research personnel.

**References**

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<table><caption>**Table 1.** Characteristics of the study population with self-reported information by negative or positive influenza test result, France, October 2024-April 2025 (n = 77,704)</caption><thead><tr><th></th><th>Characteristi<br>c</th><th>N<br>(Negative)</th><th>%<br>(Negative)</th><th>N (Positive)</th><th>% (Positive)</th><th>p-value<sup>a</sup></th></tr></thead><tbody><tr><td>PCR Results</td><td>All</td><td>57,054</td><td></td><td>20,650</td><td></td><td></td></tr><tr><td rowspan="2">Sex</td><td>Female</td><td>34,083</td><td>59.7</td><td>11,887</td><td>57.6</td><td>&lt;0.001</td></tr><tr><td>Male</td><td>22,971</td><td>40.3</td><td>8,763</td><td>42.4</td><td></td></tr><tr><td rowspan="4">Age group in<br>years</td><td>0-4</td><td>3,451</td><td>6</td><td>2,638</td><td>12.8</td><td>&lt;0.001</td></tr><tr><td>5-17</td><td>4,917</td><td>8.6</td><td>3,473</td><td>16.8</td><td></td></tr><tr><td>18-64</td><td>33,742</td><td>59.1</td><td>11,996</td><td>58.1</td><td></td></tr><tr><td>≥ 65</td><td>14,944</td><td>26.2</td><td>2,543</td><td>12.3</td><td></td></tr><tr><td rowspan="3">Vaccination<sup>b</sup></td><td>No vaccine</td><td>46,537</td><td>81.6</td><td>18,626</td><td>90.2</td><td>&lt;0.001</td></tr><tr><td>Vaccine 15<br>days-3 months</td><td>6,662</td><td>11.7</td><td>1,325</td><td>6.4</td><td></td></tr><tr><td>Vaccine 3-6<br>months</td><td>3,855</td><td>6.8</td><td>699</td><td>3.4</td><td></td></tr><tr><td rowspan="4">Influenza<br>type</td><td>A</td><td></td><td></td><td>7,982</td><td>64.8</td><td></td></tr><tr><td>B</td><td></td><td></td><td>4,283</td><td>34.8</td><td></td></tr><tr><td>A+B</td><td></td><td></td><td>56</td><td>0.5</td><td></td></tr><tr><td>PCR not<br>typed</td><td></td><td></td><td>8,329</td><td></td><td></td></tr><tr><td rowspan="5">Subtype<br>clade</td><td>A(H1N1)pdm<br>09 –<br>6B.1A.5a.2a</td><td></td><td></td><td>533</td><td>24.1</td><td></td></tr><tr><td>A(H1N1)pdm<br>09 –<br>6B.1A.5a.2a.1</td><td></td><td></td><td>53</td><td>2.4</td><td></td></tr><tr><td>A(H3N2) –<br>3C.2a1b.2a.2a.<br>3a.1</td><td></td><td></td><td>678</td><td>30.7</td><td></td></tr><tr><td>B – V1A.3a.2</td><td></td><td></td><td>948</td><td>42.9</td><td></td></tr><tr><td>Not<br>sequenced</td><td></td><td></td><td>18,438</td><td></td><td></td></tr><tr><td>Clade<br>subclade</td><td>3C.2a1b.2a.2a.<br>3a.1 – J.1.1</td><td></td><td></td><td>5</td><td>0.2</td><td></td></tr></tbody></table>
<table><tr><td>3C.2a1b.2a.2a.3a.1 - J.2</td><td>579</td><td>26.2</td></tr><tr><td>3C.2a1b.2a.2a.3a.1 - J.2.1</td><td>22</td><td>1</td></tr><tr><td>3C.2a1b.2a.2a.3a.1 - J.2.2</td><td>72</td><td>3.3</td></tr><tr><td>6B.1A.5a.2a - C.1.9</td><td>106</td><td>4.8</td></tr><tr><td>6B.1A.5a.2a - C.1.9.1</td><td>17</td><td>0.8</td></tr><tr><td>6B.1A.5a.2a - C.1.9.3</td><td>406</td><td>18.4</td></tr><tr><td>6B.1A.5a.2a - C.1.9.4</td><td>4</td><td>0.2</td></tr><tr><td>6B.1A.5a.2a.1 - D</td><td>11</td><td>0.5</td></tr><tr><td>6B.1A.5a.2a.1 - D.1</td><td>2</td><td>0.1</td></tr><tr><td>6B.1A.5a.2a.1 - D.3</td><td>35</td><td>1.6</td></tr><tr><td>6B.1A.5a.2a.1 - D.5</td><td>5</td><td>0.2</td></tr><tr><td>V1A.3a.2 - C.3</td><td>3</td><td>0.1</td></tr><tr><td>V1A.3a.2 - C.5</td><td>5</td><td>0.2</td></tr><tr><td>V1A.3a.2 - C.5.1</td><td>383</td><td>17.3</td></tr><tr><td>V1A.3a.2 - C.5.6</td><td>216</td><td>9.8</td></tr><tr><td>V1A.3a.2 - C.5.7</td><td>341</td><td>15.4</td></tr><tr><td>Not sequenced</td><td>18,438</td><td></td></tr></table>

<footnote>a Differences between negative and positive tests were tested with Pearson's chi-squared test and considered significant at the <0.001 level</footnote>

<footnote>b Vaccination is self-reported and the time intervals presented in the table are not mutually exclusive and reflect the way participants were asked to self-report since when they were last vaccinated against influenza</footnote>
<table><caption>**Table 2.** Vaccination coverage by age group reported in the RELAB Network, France, October 2024 – February 2025 (n = 77,704)</caption><thead><tr><th>Vaccine</th><th>N<br>(0-4 y)</th><th>%</th><th>N<br>(5-17 y)</th><th>%</th><th>N<br>(18-64 y)</th><th>%</th><th>N<br>(65+ y)</th><th>%</th></tr></thead><tbody><tr><td>Total</td><td>6,089</td><td></td><td>8,390</td><td></td><td>45,738</td><td></td><td>17,487</td><td></td></tr><tr><td>No vaccine</td><td>6,021</td><td>98.9</td><td>8,224</td><td>98</td><td>41,368</td><td>90.4</td><td>9,550</td><td>54.6</td></tr><tr><td>Vaccine 15<br>days-3<br>months</td><td>41</td><td>0.7</td><td>90</td><td>1.1</td><td>2,751</td><td>6</td><td>5,105</td><td>29.2</td></tr><tr><td>Vaccine 3-6<br>months</td><td>27</td><td>0.4</td><td>76</td><td>0.9</td><td>1,619</td><td>3.5</td><td>2,832</td><td>16.2</td></tr></tbody></table>

## Figure Captions

**Figure 1.** Influenza test positivity per week, for non-vaccinated individuals and individuals vaccinated (15 days to 6 months prior testing), (A) Overall activity, (B) Influenza A activity, (C) Influenza B activity, France, October 2024–April 2025 (n = 77,704)

**Figure 2.** Proportion of Influenza Types by Age Group: (A) Influenza A activity, (B) Influenza B activity, France, October 2024 – April 2025

**Figure 3.** Dynamics of clades (subclades) of sequenced influenza viruses: (A) Influenza A(H1N1)pdm09 distribution, (B) Influenza A(H1N1)pdm09 proportion, (C) Influenza A(H3N2) distribution, (D) Influenza A(H3N2) proportion, (E) Influenza B/Victoria distribution, (F) Influenza B/Victoria proportion. France, October 2024 - June 2025

**Figure 4.** Vaccine effectiveness against influenza overall, and stratified by virus type and individual characteristics: (A) Evolution of estimates across the season, (B) End-of-season estimates for individuals vaccinated 15 days to 3 months prior to testing, France, October 2024 - April 2025 (C) End-of-season estimates for individuals vaccinated 3 to 6 months prior to testing. France, October 2024 - April 2025

**Figure 5.** Vaccine effectiveness against influenza by virus type, subtype, clade and sub-clade in the study, (A) vaccination status between 15 days and 3 months prior to testing, (B) vaccination status between 3 and 6 months prior to testing, France, October 2024 - April 2025

**Figure 6.** Clade (subclades) frequencies by vaccination status for individuals vaccinated 15 days to 6 months prior to testing, (A) Influenza A(H1N1)pdm09 frequencies, (B) Influenza A(H3N2) frequencies, (C) Influenza B/Victoria frequencies. France, October 2024 - June 2025

**Figure S1.** Genetic diversity of sequenced influenza viruses, (A) Dynamics of subtype density, (B) Dynamics of subtype proportions, (C) Clade (subclade) diversity. France, October 2024 – June 2025
<figure><img src="image_11.png" /></figure>

<figure><img src="image_12.png" /></figure>

<figure><img src="image_13.png" /></figure>

<figure><img src="image_14.png" /></figure>

Age Group

0-4
5-17
18-64
65

<figure><img src="image_15.png" /></figure>

<figure><img src="image_16.png" /></figure>
A

Overall December
Overall End-of-season
Influenza B Interim
Influenza B End-of-season

Overall End-of-season
Influenza B Interim
Influenza B End-of-season

Influenza A Interim
Influenza A End-of-season
Influenza A End-of-season

Influenza A Interim
Influenza A End-of-season

<figure><img src="image_17.png" /><figcaption>A. Influenza B/Victoria distribution</figcaption></figure>

<figure><img src="image_18.png" /><figcaption>C. Influenza A(H3N2) distribution</figcaption></figure>

<figure><img src="image_19.png" /><figcaption>E. Influenza A(H1N1)pdm09 distribution</figcaption></figure>

<figure><img src="image_20.png" /><figcaption>B. Influenza B/Victoria proportion</figcaption></figure>

<figure><img src="image_21.png" /><figcaption>D. Influenza A(H3N2) proportion</figcaption></figure>

<figure><img src="image_22.png" /><figcaption>F. Influenza A(H1N1)pdm09 proportion</figcaption></figure>

A. Evolution of Vaccine Effectiveness Estimates
15 days - 6 months after vaccination

<figure><img src="image_23.png" /></figure>

B. End-of-season Vaccine Effectiveness Estimates
15 days - 3 months after vaccination

<figure><img src="image_24.png" /></figure>

C. End-of-season Vaccine Effectiveness Estimates
3 - 6 months after vaccination

<figure><img src="image_25.png" /></figure>

<figure><img src="image_26.png" /></figure>
A. Vaccine Effectiveness Estimates by Subtypes, Clades and Subclades
15 days – 3 months after vaccination

<figure><img src="image_27.png" /></figure>

B. Vaccine Effectiveness Estimates by Subtypes, Clades and Subclades
3–6 months after vaccination

<figure><img src="image_28.png" /></figure>

<figure><img src="image_29.png" /></figure>

<figure><img src="image_30.png" /></figure>

<figure><img src="image_31.png" /></figure>

<figure><img src="image_32.png" /></figure>

<figure><img src="image_33.png" /></figure>