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Research Article

Examining the potential benefits of the influenza vaccine against SARS-CoV-2: A retrospective cohort analysis of 74,754 patients

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Software, Validation, Visualization, Writing – original draft, Writing – review & editing

¶ ‡ Denotes equal contribution as co-first authors.

Affiliation Division of Plastic & Reconstructive Surgery, University of Miami Miller School of Medicine, Miami, Florida, United States of America

Roles Project administration, Resources, Software, Supervision, Writing – review & editing

Affiliation Anne Arundel Medical Center, Annapolis, Maryland, United States of America

Roles Conceptualization, Investigation, Methodology, Project administration, Supervision, Writing – review & editing

* E-mail: [email protected]

• Susan M. Taghioff, 
• Benjamin R. Slavin, 
• Tripp Holton, 
• Devinder Singh

• Published: August 3, 2021
• https://doi.org/10.1371/journal.pone.0255541
• Reader Comments

Introduction

Recently, several single center studies have suggested a protective effect of the influenza vaccine against severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). This study utilizes a continuously updated Electronic Medical Record (EMR) network to assess the possible benefits of influenza vaccination mitigating critical adverse outcomes in SARS-CoV-2 positive patients from 56 healthcare organizations (HCOs).

The de-identified records of 73,346,583 patients were retrospectively screened. Two cohorts of 37,377 patients, having either received or not received influenza vaccination six months–two weeks prior to SARS-CoV-2 positive diagnosis, were created using Common Procedural Terminology (CPT) and logical observation identifiers names and codes (LOINC) codes. Adverse outcomes within 30, 60, 90, and 120 days of positive SARS-CoV-2 diagnosis were compared between cohorts. Outcomes were assessed with stringent propensity score matching including age, race, ethnicity, gender, hypertension, diabetes, hyperlipidemia, chronic obstructive pulmonary disease (COPD), obesity, heart disease, and lifestyle habits such as smoking.

SARS-CoV-2-positive patients who received the influenza vaccine experienced decreased sepsis (p<0.01, Risk Ratio: 1.361–1.450, 95% CI:1.123–1.699, NNT:286) and stroke (p<0.02, RR: 1.451–1.580, 95% CI:1.075–2.034, NNT:625) across all time points. ICU admissions were lower in SARS-CoV-2-positive patients receiving the influenza vaccine at 30, 90, and 120 days (p<0.03, RR: 1.174–1.200, 95% CI:1.003–1.385, NNT:435), while approaching significance at 60 days (p = 0.0509, RR: 1.156, 95% CI:0.999–1.338). Patients who received the influenza vaccine experienced fewer DVTs 60–120 days after positive SARS-CoV-2 diagnosis (p<0.02, RR:1.41–1.530, 95% CI:1.082–2.076, NNT:1000) and experienced fewer emergency department (ED) visits 90–120 days post SARS-CoV-2-positive diagnosis (p<0.01, RR:1.204–1.580, 95% CI: 1.050–1.476, NNT:176).

Our analysis outlines the potential protective effect of influenza vaccination in SARS-CoV-2-positive patients against adverse outcomes within 30, 60, 90, and 120 days of a positive diagnosis. Significant findings favoring influenza vaccination mitigating the risks of sepsis, stroke, deep vein thrombosis (DVT), emergency department (ED) & Intensive Care Unit (ICU) admissions suggest a potential protective effect that could benefit populations without readily available access to SARS-CoV-2 vaccination. Thus further investigation with future prospective studies is warranted.

Citation: Taghioff SM, Slavin BR, Holton T, Singh D (2021) Examining the potential benefits of the influenza vaccine against SARS-CoV-2: A retrospective cohort analysis of 74,754 patients. PLoS ONE 16(8): e0255541. https://doi.org/10.1371/journal.pone.0255541

Editor: Corstiaan den Uil, Erasmus Medical Centre: Erasmus MC, NETHERLANDS

Received: April 29, 2021; Accepted: July 17, 2021; Published: August 3, 2021

Copyright: © 2021 Taghioff et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper.

Funding: The authors received no specific funding for this work.

Competing interests: Dr. Holton serves as a consultant for Acelity/3M and Stryker. Dr. Slavin, Ms. Taghioff, and Dr. Singh have no relevant disclosures. The authors have not received any consulting fees, stock options, research funding, capital equipment, or educational grants from TriNetX.

With cases in excess of 140 million and a death toll over 3 million, COVID-19 has greatly impacted the global community [ 1 ]. In the nascency of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), demand for rapid, yet accurate data was voracious [ 2 ]. As the world continues to attempt to overcome the current pandemic and readies itself to combat a future one, the need for expeditious clinical answers remains paramount.

Federated electronic medical record (EMR) networks, such as TriNetX (TriNetX Inc, Cambridge, MA), aggregate the de-identified records of millions of patients from participating healthcare organizations (HCOs) into an accessible and searchable database in real-time [ 3 , 4 ]. Several publications have already demonstrated the utility of federated EMR networks in addressing research questions regarding the implications of SARS-CoV-2 on maladies including obesity, rheumatological disease, gastrointestinal bleeding, and psychiatric illness [ 5 – 8 ]. The efficiency and speed with which these previous retrospective studies were able to examine topics of interest, using real-time EMRs, allows for the collective advancement of COVID-19 knowledge in hopes of optimizing prevention and management.

Recently, several studies have suggested a possible protective effect of the influenza vaccine against SARS-CoV-2 [ 9 – 12 ]. Although no cross-reactivity between influenza-induced antibodies and SARS-CoV-2 protection has been demonstrated, several theorized mechanisms of the potential protective effect of influenza vaccination have been proposed in the recent literature [ 9 , 13 , 14 ]. The first hypothesis centers around the presence of MF59 in the influenza vaccine: an oil-in-water squalene emulsion that has been shown to assist in potentiating an immune response to SARS-CoV variants [ 14 ]. Alternatively, influenza vaccination’s potential protective effect may be explained by its ability to stimulate the activation of natural killer cells, the levels of which have been found to be considerably decreased in moderate and severe SARS-CoV-2 cases [ 15 , 16 ]. Another proposed mechanism was described in a recent case-control study of 261 healthcare workers. The authors noted several prior studies that suggested both coronaviruses and influenza viruses engage with the angiotensin-converting enzyme 2 (ACE-2) and tetraspanin antibodies. Thus, there is belief that ACE-2 and tetraspanin antibodies may inhibit both coronavirus and low-pathogenic influenza A virus infections. Outcomes of this study pointed to a potential protective effect in those with influenza vaccination [ 11 ]. Additional studies reported that the influenza vaccine may lead to decreased risk of cardiovascular events due to potential interaction with immune and inflammatory systems to promote plaque stabilization [ 17 , 18 ]. It has also been recently reported that influenza vaccine-induced antibodies may interact with the bradykinin 2 receptor, leading to an anti-inflammatory effect secondary to increasing nitric oxide [ 18 , 19 ].

In a single-center study of 2,005 patients, Yang et al. were the first to perform a retrospective review highlighting a potential protective effect of influenza vaccination against adverse outcomes associated with SARS-CoV-2. Only 10.7% of patients in this study were considered up to date on their influenza immunization. The authors reported a 2.44 greater odds ratio (OR) for hospitalization and 3.29 greater OR for intensive care unit (ICU) admission indicating a protective effect for SARS-CoV-2 positive patients who were up to date on their influenza immunization [ 9 ].

This investigation seeks to explore the potential protective effects of influenza vaccination against SARS-CoV-2 using the TriNetX database. Specifically, this study aims to assess the possible benefit of influenza vaccination in mitigating critical adverse outcomes in SARS-CoV-2 positive patients using 73 million deidentified EMRs from 56 HCOs provided by a continuously updated network.

At the time of our search in January 2021, the analytics subset contained EMRs from 56 HCOs distributed predominantly throughout the United States of America, but also with participating institutions in the United Kingdom, Italy, Germany, Israel, and Singapore. Within the US, the geographic distribution of HCOs is 6% in the Northwest, 33% in the Midwest, 42% in the South, and 19% in the West [ 3 ]. The deidentified records of 73,346,583 patients were retrospectively screened using the TriNetX platform ( Fig 1 ).

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https://doi.org/10.1371/journal.pone.0255541.g001

In order to ensure accuracy, logical observation identifiers names and codes (LOINCs), the universal standard for identification of medical laboratory data, were used to identify patients positive for SARS-CoV-2 (LOINC 94500–6). CPT codes were used to identify patients who had received either the trivalent live intranasal (90660) or inactivated intramuscular influenza vaccine (90653) within a timeframe of six months–two weeks prior to receiving a SARS-CoV2-positive diagnosis. Additionally, Medicare patients receiving either the intranasal or intramuscular influenza vaccine were captured using the corresponding healthcare common procedure coding system (HCPCS) code (G0008). Any EMRs belonging to patients that were pregnant, incarcerated, experienced an outcome outside of a 120-day post-SARS-CoV-2 diagnosis window, or not meeting all of the aforementioned criteria by CPT code were excluded. Following application of inclusion and exclusion criteria, a cohort of 2,814,377 patients who had not received the influenza vaccine six months–two weeks prior to a positive SARS-CoV-2 diagnosis was compared to a second cohort of 37,377, patients who had received the influenza vaccine six months–two weeks prior to a positive SARS-CoV-2 diagnosis. We selected two weeks as the minimum end of our study’s timespan as it takes approximately two weeks for the immune system to fully develop antibodies following influenza vaccination. Conversely, six months was chosen as the maximum end of the timespan between influenza vaccination and SARS-CoV-2-positive diagnosis because the accepted standard for adequate protection without a waning effect is six months [ 20 ].

Following the creation of these two cohorts, we used the TriNetX platform to facilitate propensity score matching between cohorts with ICD-10 codes for numerous factors including age, race, gender, ethnicity, diabetes mellitus (E08-E13), elevated BMI status (E65-E68), hypertension (I10-I16), chronic ischemic heart disease (I25), heart failure (I50), COPD (J44), musculoskeletal disease (M00-M99), and factors influencing health status and contact with human services (Z00-Z99) which includes factors influencing health status including tobacco use, body mass index (BMI), and socioeconomic status. After propensity score matching, a cohort of 37,377 SARS-CoV-2 positive patients without influenza vaccination was paired with a second cohort of 37,377 SARS-CoV-2 positive patients, comparable in demographics and co-morbidities, that had received influenza vaccination within the aforementioned time frame.

Propensity score 1:1 balancing was completed within the TriNetX platform via logistic regression utilizing version 3.7 of Python Software Foundation’s Scikit-Learn package (Python Software Foundation, Delaware, USA). A greedy nearest neighbor matching algorithm approach was used, setting standard differences to a value of less than 0.1 to indicate appropriate matching. To eliminate record order bias, randomization of the record order in a covariate matrix occurs before matching. Baseline characteristics with a standardized mean difference between cohorts lower than 0.1 were considered well balanced.

Following optimization of the two cohorts for direct comparison, adverse outcomes were identified with ICD-10 or CPT codes as sepsis (A41.9), deep vein thrombosis (DVT) (I82.220, I82.40-I82.89, I82.A19), pulmonary embolism (I26), acute myocardial infarction (I21), stroke(I63), arthralgia(M25.5), ICU admission (99291, 1013729, 1014309), ED visits (1013711), hospital admission (1013659, 1013660, 1013699), renal failure (N19), acute respiratory distress syndrome (J80), acute respiratory failure (J96), anorexia (R63), pneumonia (J18), and death. Following identification, adverse outcomes within 30, 60, 90, and 120 days of SARS-CoV-2-positive diagnosis were analyzed and compared between the two cohorts. 120 days was made the maximum endpoint of our study window to account for the presence of the poorly understood Post-Acute Covid Syndrome (PACS), an autonomic dysfunction phenomenon observed in many patients after recovering from SARS-CoV-2 [ 17 ].

Using the TriNetX platform’s Analytics function, statistical analysis and logistical regression were performed by comparing indices and relative risks of outcomes following the successful matching of cohorts with a p-value greater than 0.05. Outcomes for all measures were calculated using 95% confidence intervals (CIs). All p-values were two-sided and the alpha level was set at 0.05. Risk ratio was defined in this study as the ratio of the probability of an adverse SARS-CoV-2-related event occurring without history of up-to-date influenza vaccination versus the probability of the same adverse SARS-CoV-2-related event occurring in a patient with history of up-to-date influenza vaccination [ 21 ].

Subsequently, Absolute Risk Reduction (ARR), defined as the difference in risk of an adverse SARS-CoV-2-related outcome between the influenza-vaccinated group and non-influenza-vaccinated group, was calculated for each adverse outcome. The reciprocal of ARR was then obtained to determine number needed to treat, henceforth referred to in this study as number needed to vaccinate (NNV), for all statistically significant variables. The NNV is a calculation specifying the average number of patients who needed to be up-to-date on their influenza vaccination in order to have prevented one adverse SARS-CoV-2-related outcome [ 22 , 23 ].

Propensity score matching resulted in 37,377 patients in each cohort. Prior to matching, all between-groups factors were found to be significantly different (p<0.0001). However, following matching, all demographic and diagnostic factors were no longer significant (p>0·05) ( Table 1 ), indicating successful balancing.

https://doi.org/10.1371/journal.pone.0255541.t001

Following propensity score matching by the TriNetX system, statistical analysis was performed for all adverse outcomes of interest at 4 time points: 30, 60, 90, and 120 days following a SARS-CoV-2-positive diagnosis (Tables 2 – 5 ).

https://doi.org/10.1371/journal.pone.0255541.t002

https://doi.org/10.1371/journal.pone.0255541.t003

https://doi.org/10.1371/journal.pone.0255541.t004

https://doi.org/10.1371/journal.pone.0255541.t005

SARS-CoV-2-positive patients who received the influenza vaccine experienced significantly decreased sepsis (p = 0.0001–0.0020, Risk Ratio: 1.361–1.450, 95% CI: 1.123–1.699) and stroke (p = 0.0003–0.0154, Risk Ratio: 1.451–1.580, 95% CI: 1.075–2.034) across all time points. ICU admissions were significantly lower in SARS-CoV-2-positive patients receiving the influenza vaccine at 30, 90, and 120 days (p = 0.0073–0.0240, Risk Ratio: 1.174–1.200, 95% CI: 1.003–1.385), while approaching significance at 60 days (p = 0.0509, Risk Ratio: 1.156, 95% CI: 0.999–1.338) ( Fig 2A ).

Significant adverse outcome trends 30–120 days (a), 60–120 days (b) & 90–120 days (c) (p<0.05). ** ICU Admissions Within 60 Days approaching significance (p = 0.0509, 95%).

https://doi.org/10.1371/journal.pone.0255541.g002

Patients who received influenza vaccination experienced significantly fewer DVTs 60–120 days after positive SARS-CoV-2 diagnosis (p = 0.0058–0.0108, Risk Ratio: 1.411–1.530, 95% CI: 1.082–2.076) ( Fig 2B ) and experienced significantly fewer ED visits 90–120 days post SARS-CoV-2-positive diagnosis (p = 0.0001–0.0076, Risk Ratio: 1.204–1.580, 95% CI: 1.050–1.476) ( Fig 2C ).

Additional findings included patients up-to-date on their influenza vaccination experiencing significantly less anorexia within 90 days of SARS-CoV-2-positive diagnosis (p = 0.0486, Risk Ratio: 1.276, 95% CI: 1.001–1.627) as well as decreased arthralgia within 120 days of SARS-CoV-2-positive diagnosis (p = 0.0041, Risk Ratio: 1.218, 95% CI: 1.064–1.395).

NNV with influenza vaccination to prevent one adverse SARS-CoV-2-related outcome calculations for significant findings for sepsis, stroke, and ICU Admission within 30, 60, 90, and 120 days of positive SARS-CoV-2 diagnosis are illustrated in Fig 3 , along with NNV to prevent DVT within 60–120 days, and NNV to prevent ED Visits within 90–120 days ( Fig 3 ).

https://doi.org/10.1371/journal.pone.0255541.g003

This study underscores the utility of federated EMR networks as a potential solution for the need for urgent clinical data, particularly during health crises such as pandemics. While the work of retrospective single-center studies continues to have advantages such as detailed historical patient information that deidentified EMR networks cannot provide, the ability to scan, in minutes, the charts of 73 million patients from 56 HCOs in real-time to guide clinical decision-making is invaluable.

EMRs included in our study monitored patients with positive SARS-CoV-2 diagnoses for adverse outcomes during a period of 120 days. This time window was chosen intentionally to account for the possible presence of PACS. Although poorly understood, previous studies of PACS have reported orthostatic intolerance, often without objective hemodynamic abnormalities upon testing, as well as new illness-related fatigue to be the most common presentations. Development of these symptoms was found to occur between 0–122 days and 29–71 days post-SARS-CoV-2 diagnosis respectively [ 24 , 25 ].

By focusing on rates of hospitalization and ICU admission, the study of Yang et al., garnered a sizable amount of media coverage [ 23 , 24 ]. This study most closely mirrors this study’s aim of appraising the potential impact of influenza vaccination on adverse outcomes associated with SARS-CoV-2. Prior to comparing findings between these two studies, it is important to note several key differences in methodology [ 9 ]. While both studies relied on medical coding to identify SARS-CoV-2 positivity and influenza vaccination status, the timeframes were different, with this study encompassing the first full year of SARS-CoV-2 cases globally from January 2020-January 2021 [ 1 , 25 ]. This timespan enabled our study to include data from the 2019–2020 influenza vaccine formulation as well as the most recent 2020–2021 influenza season formulation. This contrasts with the timespan of the previously mentioned study, as well as the recently published retrospective review of 27,000 patients by Conlon et al. Both of these studies analyzed SARS-CoV-2 cases between March-August 2020, a period overlapping between two different influenza vaccinations and seasons which excludes peak influenza season, and did not set a 2 week– 6 month time limit for influenza vaccine being “current/active” [ 9 , 12 ]. Additionally, the Yang and Conlon study timeframes began 6 months after the CDC’s recommended influenza vaccination time in October, therefore the vaccine antibodies were likely already waning [ 9 , 12 , 20 ].

Our study found no association between influenza vaccination and risk of death in SARS-CoV-2-positive patients. This confirms the previous findings of Umasabor-Bubu et al., Pedote et al. and Ragni et al., which found that a history of influenza vaccination did not confer protection against death in reviews of 558, 664, and 17,600 patients respectively [ 26 – 28 ].

Alternatively, two macro-scale studies have found there to be conflicting relationships between influenza vaccination and mortality in the elderly population. In a large scale study of over 2,000 counties in the United States, Zanettini et al. demonstrated a potential protective effect of influenza vaccination on SARS-CoV-2 mortality [ 29 ]. Conversely, Wehenkel et al. performed a macro-scale study of association between influenza vaccination rate and SARS-CoV-2 deaths in an examination of over 500,000 patients across 39 countries [ 30 ]. This study showed a positive association between COVID-19 deaths and influenza vaccination rates in elderly people 65 years of age and older. The conflicting findings of these studies may be attributable to their large scale nature and lack of analysis of individual patient EMRs, thereby further increasing the need for prospective randomized control studies to better define the potential protective effect of influenza vaccination against SARS-CoV-2.

In light of the over 140 million confirmed positive cases worldwide 1 , the use of NNV calculations allows for a deeper appreciation of the potential benefit of influenza vaccination. In addition to guarding against a possible “twindemic” of simultaneous outbreaks of influenza and SARS-CoV-2 [ 31 ], the NNV trends observed within 30–120 days of SARS-CoV-2 diagnosis for sepsis, stroke, ICU admission, DVT, and ED visits further strengthen the case in favor of a protective effect of influenza vaccination ( Fig 3 ). Specifically, in order to prevent one individual from visiting the ED, developing sepsis, being admitted to the ICU, suffering a stroke, or having a DVT within 120 days of positive SARS-CoV-2 diagnosis, 176, 286, 435, 625, and 1,000 people respectively would need to have been up-to-date with their influenza vaccination. When considered on a global scale, the NNVs calculated in this study may serve to benefit not only those that will be infected with SARS-CoV-2, a diagnosis that has already affected over 140 million to date, but also the finances and resources of the health systems responsible should patients suffer these adverse outcomes [ 32 ]. Even more encouraging, apart from DVT for which NNV remained stable, the NNVs for sepsis, stroke, ICU Admissions, and ED Visits were down trending at the 120-day mark, implying that the NNV and thus potential protective benefit of influenza vaccination may be even stronger than observed in the present study.

Expanding upon our prospective understanding of the relationship between influenza vaccination and protection against adverse outcomes during SARS-CoV-2 is the work of Pawlowski et al. This retrospective review found that a history of eight different vaccines including Polio, H. influenzae type-B, measles-mumps-rubella, and Varicella, amongst others, within the past one, two, or five years is associated with decreased SARS-CoV-2 infection rates, even after cohort balancing [ 33 ]. This suggests that the protective effect observed by our group and others against SARS-CoV-2 may not be unique to influenza vaccination.

This study has the benefits of large cohort size and a tightly matched patient population, however reliance on a global database also introduces limitations that must be acknowledged. These limitations include our study’s retrospective nature, absence of detailed historical patient data, and lack of ability to follow up regarding new symptoms. Our search query’s reliance on the CPT, ICD-10, and LOINC coding of individual HCOs is another potential source of confounding as the accuracy of these factors is inherent to the EMRs comprising the database. This statement is particularly of interest as relates to false positive and false negative cases of SARS-CoV-2, which relies on the specificity and sensitivity of PCR and rapid antigen testing.

Federated EMR networks, such as TriNetX, have vast potential to challenge or verify scientific findings using sample sizes and turnaround times unachievable by individual centers, particularly during health crises such as pandemics. Our study was able to verify and challenge the relatively large difference in the potential protective effect of influenza vaccination observed by the previous study with a much more modest effect backed by nearly 75,000 global EMRs [ 9 ]. The potential protective effects of the vaccine against sepsis, stroke, DVT, ED visits, and ICU admissions at 30, 60, 90, and 120 days following SARS-CoV-2-positive diagnosis reaffirms the importance of annual influenza immunization.

While this observed potential protective effect is relatively small, the stringently matched cohort balancing and sample size afforded by TriNetX substantially increases our confidence in the fidelity of our findings. In the context of over 140 million cases globally, the potential protective benefits further elucidated by the NNV calculations for these same adverse outcomes suggests that a concerted effort to continue ramping up influenza vaccination in parallel with SARS-CoV-2 vaccination is strongly worth consideration. Although production and distribution of SARS-CoV-2 vaccines continues to increase daily, the fact remains that certain populations in the global community may still have to wait a long period of time before they are vaccinated and could therefore benefit from a more readily available source of even marginally increased protection [ 34 ]. That being said, less than half of US adults receive influenza vaccination each year, with Non-Hispanic Black, Hispanic, and American Indian/Alaskan Native individuals having had the lowest influenza vaccination coverage while also being disproportionately affected by SARS-CoV-2 [ 35 ].

The influenza vaccine may be a viable option to attenuate the adverse effects of SARS-CoV-2 worldwide, with a specific potential to benefit populations struggling with access to or distribution of SARS-CoV-2 vaccination. Even patients who have already received SARS-CoV-2 vaccination may stand to benefit given that the SARS-CoV-2 vaccine does not convey complete immunity, although further research into the relationship and potential interaction between influenza vaccination and SARS-CoV-2 vaccination should be performed.

Using a federated EMR network of over 73 million patients across 56 global HCOs, this analysis examines the potential protective effect of the influenza vaccine against various adverse outcomes at 30, 60, 90, and 120 days of SARS-CoV-2-positive diagnosis. Significant findings in favor of the influenza vaccine in mitigating the risks of sepsis, stroke, DVT, ED visits, and ICU admissions suggest a protective effect that merits further investigation. Limitations include this study’s retrospective nature and its reliance on the accuracy of medical coding. Future prospective controlled studies to validate these findings and determine if an increased emphasis on influenza vaccination will improve adverse outcomes in SARS-CoV-2-positive patients will be beneficial.

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Influenza Vaccine

• 1 Fishbein Fellow, JAMA
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The influenza vaccine, commonly called the “flu shot,” helps decrease the likelihood of becoming sick with seasonal viruses that cause influenza.

Influenza viruses, spread by coughing and sneezing, circulate yearly in the US from late fall through early spring. Influenza typically causes an acute short-lived illness but can be fatal, especially in high-risk people. Between 2016 and 2019, influenza is estimated to have caused 34 200 to 61 000 deaths in the US each season.

What Are the Different Types of Influenza Vaccines?

There are 3 types of influenza vaccines: inactivated, recombinant, and live-attenuated. The recommended vaccine type depends on a patient’s age and health. The 2020-2021 season’s inactivated influenza vaccines, given by intramuscular injection, will contain inactive components of 4 different influenza viruses. These inactivated influenza vaccines are approved for people aged 6 months or older. Higher-dose inactivated influenza vaccines will be offered to people aged 65 years or older. A recombinant influenza vaccine, manufactured without influenza viruses or eggs, will be available for people aged 18 years or older. Live-attenuated influenza vaccine, given as a nasal spray, is approved for people with a normally functioning immune system who are 2 to 49 years old.

Who Should Have an Influenza Vaccination and When?

Because influenza viruses mutate each year, influenza vaccination is recommended every fall for all people aged 6 months or older unless they have had a severe allergic reaction to influenza vaccination. Ideally, the vaccine is given before the end of October, but it should be offered to all unvaccinated people throughout the influenza season. If vaccine supply is low, priority should be given to people at high risk of complications from influenza, including older adults, pregnant women, very young children, and those with certain chronic medical conditions or immunocompromised states. Health care workers and caregivers should also be vaccinated to decrease the likelihood of transmitting influenza to vulnerable people.

How Effective Is the Influenza Vaccine?

The effectiveness of influenza vaccination varies each year depending on the types of actively circulating influenza viruses, the match between the virus and the influenza vaccine, and the age and health of people exposed. In 2017-2018, influenza vaccination is estimated to have prevented 7.1 million illnesses, 109 000 hospitalizations, and 8000 deaths.

Is the Influenza Vaccine Safe?

The inactivated, recombinant, and live-attenuated influenza vaccines are all considered very safe. The most common side effect from intramuscular influenza vaccination is soreness at the injection site. In certain influenza seasons, the inactivated influenza vaccines have been associated with a slightly increased risk of a rare neurologic condition called Guillain-Barré syndrome. The most frequent side effects from live-attenuated vaccines are nasal congestion, headache, and sore throat. The live vaccine should be used with caution in patients with asthma because of possible increased risk of wheeze.

People with serious egg allergies may receive the recombinant or live-attenuated influenza vaccine or an inactivated influenza vaccine while under close monitoring.

For More Information

Centers for Disease Control and Prevention www.cdc.gov/flu/index.htm

Published Online: August 28, 2020. doi:10.1001/jama.2020.16846

Conflict of Interest Disclosures: None reported.

Sources: Grohskopf LA, Liburd LC, Redfield RR. Addressing influenza vaccination disparities during the COVID-19 pandemic. JAMA . Published online August 20, 2020. doi:10.1001/jama.2020.15845

Grohskopf LA, Alyanak E, Broder KR, et al. Prevention and control of seasonal influenza with vaccines: recommendations of the Advisory Committee on Immunization Practices—United States, 2020-21 influenza season. MMWR Recomm Rep. 2020;69(8):1-24. doi:10.15585/mmwr.rr6908a1

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Walter K. Influenza Vaccine. JAMA. 2020;324(14):1476. doi:10.1001/jama.2020.16846

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ORIGINAL RESEARCH article

Trivalent mrna vaccine-candidate against seasonal flu with cross-specific humoral immune response.

• 1 Federal State Budget Institution “National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N. F. Gamaleya” of the Ministry of Health of the Russian Federation, Moscow, Russia
• 2 Department of Virology, Lomonosov Moscow State University, Moscow, Russia
• 3 Department of Medical Genetics, I. M. Sechenov First Moscow State Medical University, Moscow, Russia
• 4 Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry of the Russian Academy of Sciences, Moscow, Russia
• 5 Belozersky Institute of Physico-Chemical Biology, Lomonosov Moscow State University, Moscow, Russia
• 6 Faculty of Bioengineering and Bioinformatics, Lomonosov Moscow State University, Moscow, Russia
• 7 Translational Medicine Research Center, Sirius University of Science and Technology, Sochi, Russia
• 8 Infectiology Department, I. M. Sechenov First Moscow State Medical University, Moscow, Russia

Seasonal influenza remains a serious global health problem, leading to high mortality rates among the elderly and individuals with comorbidities. Vaccination is generally accepted as the most effective strategy for influenza prevention. While current influenza vaccines are effective, they still have limitations, including narrow specificity for certain serological variants, which may result in a mismatch between vaccine antigens and circulating strains. Additionally, the rapid variability of the virus poses challenges in providing extended protection beyond a single season. Therefore, mRNA technology is particularly promising for influenza prevention, as it enables the rapid development of multivalent vaccines and allows for quick updates of their antigenic composition. mRNA vaccines have already proven successful in preventing COVID-19 by eliciting rapid cellular and humoral immune responses. In this study, we present the development of a trivalent mRNA vaccine candidate, evaluate its immunogenicity using the hemagglutination inhibition assay, ELISA, and assess its efficacy in animals. We demonstrate the higher immunogenicity of the mRNA vaccine candidate compared to the inactivated split influenza vaccine and its enhanced ability to generate a cross-specific humoral immune response. These findings highlight the potential mRNA technology in overcoming current limitations of influenza vaccines and hold promise for ensuring greater efficacy in preventing seasonal influenza outbreaks.

1 Introduction

Seasonal influenza is a highly contagious respiratory disease caused by influenza A and B viruses that circulate around the world. Globally, influenza causes ~1 billion cases of illness, 3 to 5 million cases of severe illness, and up to 500,000 deaths annually ( 1 ). Pregnant women, children aged 6 months to 5 years, elderly people (aged more than 65 years), individuals with chronic disease, and healthcare workers are at increased risk of severe illness and serious complications from influenza virus infection ( 2 , 3 ). A comprehensive study employing regression models revealed that the mortality rate associated with influenza between 1990 and 2017 was most pronounced among individuals over 70 years old, with a rate of 16.4 deaths per 100,000 (95% CI 11.6-21.9) ( 4 ). Vaccination remains the primary strategy for reducing the incidence of influenza.

Various types of flu vaccines are available, including live attenuated, inactivated (whole virion, split, subunit), and recombinant vaccines ( 5 ). The effectiveness of these vaccines (i.e. their ability to provide protection against influenza) may vary from season to season. At least two factors determine the likelihood of vaccine efficacy: (i) characteristics of the individual being vaccinated, such as age and health status, and (ii) the degree of matching between the vaccine composition and the influenza strains currently circulating in the human population ( 6 ). Currently, most influenza vaccines are either quadrivalent (containing antigens of the H1N1 and H3N2 strains of influenza A combined with two lineages of influenza B, including the Victoria and Yamagata variants), or trivalent (containing the influenza A antigens of the H1N1 and H3N2 subtypes and one of the two influenza B subtypes) ( 7 ). According to the CDC, in seasons when vaccine antigens matched circulating influenza viruses, vaccination reduced the risk of doctor visits related to influenza by 40% to 60% ( 8 ). A 2021 study reported that among adults, vaccination was associated with a 26% lower risk of intensive care unit (ICU) admission and a 31% lower risk of death from influenza compared with those who were not vaccinated ( 9 ). From 2010 to 2012, vaccination led to a 74% reduction in the risk of influenza-related ICU admissions in children ( 10 ), and according to a 2017 study, vaccination reduced the risk of influenza-related hospitalizations in older adults by an average of 40% between 2009 and 2016 ( 11 ). Thus, vaccine prevention of influenza is both effective and justified.

In contrast, in instances where there were errors in selecting the appropriate antigenic composition, the efficacy of the vaccine was significantly compromised. A notable example was the 2017/18 vaccine, which exhibited low efficacy (~25%) in the UK due to a mismatch with the predominant influenza A strain ( 11 ). A similar decrease in effectiveness (to as low as 13%) relative to the H3N2 component of the vaccine was observed during the 2014-2015 season ( 12 ). Throughout the history of influenza vaccination, there have been numerous occurrences of such mismatches, resulted in elevated rates of severe illness and mortality from influenza in certain seasons. To mitigate the impact of seasonal and pandemic influenza on public health, there is a need for vaccines that would offer broader and more reliable protection ( 13 ).

Different approaches and platforms have been employed in the development of new influenza vaccines, including virus-like particles, DNA/mRNA vaccines, baculovirus expression system, viral vectors, et al. Of particular interest are mRNA-based vaccines, which have demonstrated their efficacy and safety during the COVID-19 pandemic ( 14 , 15 ). To date, a high immunogenicity of candidate mRNA influenza vaccines in animals and humans have been reported in a few studies ( 16 – 19 ). In particular, immunization of mice with an mRNA candidate vaccine containing mRNAs encoding twenty hemagglutinins (HAs) of various influenza virus strains led to the formation of a prolonged humoral response to all twenty HAs ( 16 ). Notably, the multivalent vaccine showed robust protection in animal models (mice, ferrets) when challenged with H1N1 influenza strains that varied in their similarity to the vaccine strain. The authors reported no mortality among vaccinated animals and observed a reduced disease severity (clinical scores) and a significantly lower weight loss compared to the control group ( 16 ).

A team led by G. Ciaramella has conducted extended preclinical and phase I clinical trials to evaluate the immunogenicity of modified mRNA encoding HA proteins from avian influenza viruses (H7 and H10) formulated in lipid nanoparticles (LNP) ( 19 ). In mice, these vaccines demonstrated a 2-5-fold increase in hemagglutination inhibition assay (HAI) titers on day 21 after immunization, which remained at a consistent level throughout the year. The protective effect of the H7-mRNA was observed even with a minimal vaccine dose (0.4 μg per mouse), although it strongly depended on the period between immunization and infection (shorter intervals led to more rapid weight loss and their death from infection in vaccinated animals). Immunization of non-human primates with a single dose of 400 μg of H10- or H7-mRNA generated an immune response with HAI titers in serum ranging from 1:100 to 1:1 000; two weeks after repeated immunization, HAI titers reached 1:1 000 000. In two randomized, double-blind, placebo-controlled phase 1 studies involving healthy volunteers (n=201 for H10-mRNA and n=165 for H7-mRNA), the vaccines demonstrated favorable safety and reactogenicity profiles, as well as a robust humoral immune response ( 20 ). Following double intramuscular immunization with 100 µg of H10-mRNA, all volunteers exhibited serum HAI titers exceeding 1:40, and 87% of participants showed microneutralization reaction titers of ≥1:20. For H7-mRNA, intramuscular administration of 10, 25, and 50 µg doses led to HAI titers exceeding ≥1:40 in ~36%, 96%, and 90% of participants, respectively. At the same time, no significant HA-specific cellular immune response was observed in the IFN-γ ELISPOT assay ( 20 ).

Despite the growing body of research on the immunogenicity of mRNA vaccines against influenza, there is still a limited understanding of their potential to elicit a broad immune response against influenza strains with varying degrees of homology. In this study, we addressed this issue by presenting our own experience in the development of a trivalent mRNA flu vaccine and exploring its immunogenicity and protective efficacy in a mouse model. Through a two-dose immunization of mice, we observed not only a robust humoral immune response, but also cross-reactivity of this response against heterologous strains of the influenza virus.

2 Materials and methods

2.1 mrna production.

The pJAZZ-OK-based linear bacterial plasmids (Lucigen) with coding regions of every HAs were used as templates for mRNAs production. DNA cloning procedures were performed as described earlier ( 21 ). The identity of the coding sequences was confirmed by Sanger sequencing. The pDNA for IVT were isolated from the E.coli BigEasy™-TSA™ Electrocompetent Cells (Lucigen) using the Plasmid Maxi Kit (QIAGEN). The pDNA was digested using BsmBI-v2 restriction endonuclease (NEB), followed by purification of the product by phenol-chloroform extraction and ethanol precipitation. IVT was performed as described earlier ( 21 ). Briefly, 100-μl reaction volume contained 3 μg of DNA template, 3 μl T7 RNA polymerase (Biolabmix) and T7 10X Buffer (TriLink), 4 mM trinucleotide cap 1 analog (3′-OMe-m7G)-5′-ppp-5′-(2′-OMeA)pG (Biolabmix), 5 mM m1ΨTP (Biolabmix) replacing UTP, and 5 mM GTP, ATP and CTP. After 2 h incubation at 37°C, 6 μl DNase I (Thermo Fisher Scientifiс) was added for additional 15 min, followed by mRNA precipitation with 2M LiCl (incubation for 1 h in ice and centrifugation for 30 min at 14,000 g, 4°C) and carefully washed with 80% ethanol. RNA integrity was assessed by electrophoresis in 8% denaturing PAGE.

2.2 mRNA-LNP assembly

LNP assembly was performed as described earlier ( 21 ) with some modifications. In brief, all lipid components were dissolved in ethanol at molar ratios 46.3:9:42.7:1.6 (ionizable lipid:DSPC:cholesterol:PEG-lipid). Acuitas ionizable lipid (ALC-0315) and PEG-lipid (ALC-0159) were purchased in Cayman Chemicals. The lipid mixture was combined with an acidification buffer of 10 mM sodium citrate (pH 3.0) containing mRNA (0.2 mg/mL) at a volume ratio of 3:1 (aqueous: ethanol) using the NanoAssemblr Ignite device (Precision NanoSystems). The ratio of ionizable nitrogen atoms in the ionizable lipid to the number of phosphate groups in the mRNA (N:P ratio) was set to 6 for each formulation. Formulations were dialyzed against PBS (pH 7.2) in Slide-A-Lyzer dialysis cassettes (Thermo Fisher Scientific) for at least 24 h. Formulations were passed through a 0.22-μm filter and stored at 4°C (PBS) until use. The diameter and size distribution, zeta potential of the mRNA-LNP were measured using a Zetasizer Nano ZS instrument (Malvern Panalytical) according to user manual.

The mRNA encapsulation efficiency and concentration were determined by SYBR Green dye (SYBR Green I, Lumiprobe) followed by fluorescence measurement. Briefly, mRNA-LNP samples were diluted with TE buffer (pH 8.0) in the absence or presence of 2% Triton-X-100 in a black 96-well plate. Standard mRNA (4 ng/μL) was serially diluted with TE buffer in the absence or presence of 2% Triton-X-100 to generate standard curves. Then the plate was incubated 10 min at room temperature on a rotating shaker (260 rpm) followed by addition of SYBR Green dye (100 times diluted in TE buffer) to each well to bind RNA. Fluorescence was measured at 454 nm excitation and 524 nm emission using Varioscan LUX (Thermo Fisher Scientifiс). The concentrations of mRNA after LNP disruption by Triton-X-100 (C total mRNA ) and before LNP disruption (C outside mRNA ) were determined using the corresponding standard curves. The concentration of mRNA loaded into the LNP was determined as the difference between the two concentrations multiplied by the dilution factor of the original sample. Encapsulation efficiency was calculated by the formula:

2.3 Cell culture

HEK293 cells (ATCC CRL-1573) were cultured in Dulbecco’s modified Eagle’s medium (DMEM, Paneco) supplemented with 2 mM L-Glutamine (Gibco), 10% fetal bovine serum (HyClone), 50 U/mL penicillin and 50 μg/mL streptomycin (both from Paneco). Transfection of HEK293 cells with H1N1 HA-encoding mRNA was performed as described previously ( 21 ) with minor modification. Briefly, HEK293 cells were plated on a 12-well plate in a density of 2×10 5 cells per well and maintained at 37°C in 5% CO 2 . The next day the medium was replaced with a fresh DMEM without antibiotics and cells were transfected by HA-mRNA using Lipofectamine 3000 reagent (Invitrogen) and Opti-Mem I Reduced Serum Medium (Gibco) in accordance with the manufacturer’s instructions. 24 h after transfection, cells were analyzed by immunocytochemical staining.

2.4 Immunocytochemistry (ICC)

For the analysis of the HA expression in the transfected HEK293 cells, they were fixed in 4% PFA (paraformaldehyde) for 30 min at 40°C, washed with PBS and permeabilized in 0.1% Triton X-100. The cells were then incubated with primary goat Anti-Influenza A Antibody (Chemicon ® , Sigma-Aldrich, #AB1074) in PBS with 0.1%/0.02% BSA/Triton X-100 at 40°C overnight. The next day, cells were incubated with Donkey Anti-Goat IgG H&L (Alexa Fluor ® 488) (ab150133; Abcam) secondary antibodies for 1 h at room temperature. Nuclei were stained with 4,6-diamidino-2-phenylindole (DAPI) (300 nM). Images were acquired on ZOE Fluorescent Cell Imager (Bio-Rad).

2.5 Viruses

Influenza virus propagation in embryonated chicken eggs or MDCK cells was performed according to conventional technique as described earlier ( 22 , 23 ). Briefly, specific pathogen-free (SPF) fertilized 9-10 days old chicken eggs were purchased from Nursery “Podmoklovo” (Russia). Presence of the embryo was monitored using an egg candler. Virus inoculation is carried out by injection of virus stock into the allantoic cavity using a needle. After 2 days of incubation at 34°C, the eggs are cooled for at least 4 h at 4°C. The eggshell above the air sac and the chorioallantoic membrane are then carefully opened, and the allantoic fluid containing the virus is harvested. The fluid is cleared from debris by centrifugation, aliquoted and transferred to -80°C for long-term storage. Virus titer was determined by endpoint dilution assay on MDCK cells as previously described ( 23 ).

2.6 Animal studies

Females BALB/c mice of 4-5 weeks old were used for the immunogenicity study of HA-mRNA-LNPs and for the viral challenge experiments. Animals were purchased from Stolbovaya breeding and nursery laboratory (Research Center for Biomedical Technologies of FMBA; Russia). All animal experiments were performed in accordance with the Directive 2010/63/EU, FELASA recommendations ( 24 ), and the Inter-State Standard of “GLP” ( 25 ) approved by the Institutional Animal Care and Use Committee (IACUC) of the Federal Research Centre of Epidemiology and Microbiology named after Honorary Academician N.F. Gamaleya and were performed under Protocol #41 from 6 April 2023. All persons using or caring for animals in research underwent training annually as required by the Biomedical Ethics Committee.

2.7 Immunizations

For mouse intramuscular immunization 100 μl of vaccine was injected in either the left or right hindlimb muscles. Mice received two doses of HA-mRNA-LNPs (altogether or apart) with a 14- or 21-days interval, while the placebo group received PBS. Mice from the positive control group were injected by equal volume (100 μl) of 1/10 human dose of split inactivated influenza vaccine.

2.8 Hemagglutinin inhibition (HAI) assay

Immunogenicity in animal experiments was estimated by hemagglutinin inhibition assay, according to the World Health Organization (WHO)-based HAI protocol ( 26 ). Shortly, mouse sera were treated by a receptor destroying enzyme (RDE produced from Vibrio cholerae was purchased from Denka Seiken Co., Ltd., Tokyo, Japan), then twofold dilutions of treated sera to be tested are made in 96 well plates. The viral antigen was added, and the plate was incubated for 30 minutes at room temperature. Human red blood cells (RBC) type O are then added and the plate incubated for a further 60 minutes at room temperature. If there were antibodies in the serum sample that cross-reacted with the virus, the antibodies would bind to the virus and prevent the virus from hemagglutinating the RBC. After incubation, the HAI titer was red as the highest dilution of serum that inhibited hemagglutination. Antigens of influenza virus for HAI test (A/Darwin/9/2021, A/Victoria/2570/2019, A/Wisconsin/588/2019, B/Austria/1359417/2021, B/Phuket/3073/2013) were purchased in LLC “Company for the production of diagnostic drugs” (St-Petersburg, Russia) or propagated in embryonated chicken eggs (A/California/07/2019 pdm09, B/Washington/02/2019) or propagated in MDCK cells (A/Guangdong-Maonan/SWL1536/2019, A/Moscow/52/2022).

2.9 HA domain ELISAs

ELISA plates (96-well; Servicebio) were coated with 100 μL of recombinant proteins in PBS at 1 μg/mL and incubated overnight at 4°C. The day of the experiment, plates were blocked with 150 μL of S002X buffer (Xema, Moscow, Russia) and incubated 2 h at room temperature. Five-fold serial dilutions of samples in ELISA buffer S011 (Xema, Moscow, Russia) were added to the plates and allowed to incubate for 1 h at 37°C (initial sample dilution 1:10). Plates were then incubated with peroxidase-conjugated goat anti-mouse IgG (L20/01; HyTest; 1:25000) for 1 h at 37°C. After final wash chromogen substrate solution R055 (Xema, Moscow, Russia) was added to each well, and the reaction was then stopped with the addition of 100 mM HCl solution. Absorbance was read at 450 nm using plate reader (Multiscan FC, Thermo Scientific). Plates were washed 3 times after first incubation and 6 times after second incubation with wash buffer S008 (Xema, Moscow, Russia). A modified trimeric HA stem domain (influenza H1N1 A/Brisbane/59/2007) was a gift from Dr. Dmitry V. Shcheblyakov from the laboratory of immunobiotechnology of the National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N. F. Gamaleya previously described at ( 27 ). The HA head domain (HA1 subunit of influenza A H1N1 A/California/04/2009) were purchased (Cat. 11055-V08H4 Sino Biological).

2.10 Viral challenge

The lethal infection caused by influenza virus was performed on 4-5-week-old female BALB/c mice. Mouse adapted influenza virus H1N1 A/Victoria/2570/2019 was obtained from the laboratory of molecular biotechnology of the Federal Research Centre of Epidemiology and Microbiology named after Honorary Academician N.F. Gamaleya. Mice were infected intranasally with 50 µL of virus suspension under Zoletil-Xylazine anesthesia. Animals were monitored for clinical symptoms (weight loss, survival) every day through 10 days after the challenge. Assessment of clinical symptoms was carried out in accordance with the scale: score of 0 (no symptoms), score of 1 (mild symptoms), score of 2 (moderate symptoms), score of 3 (severe symptoms = humane endpoint). Time of death was defined as the time at which a mouse was found dead or was euthanized via carbon dioxide asphyxiation followed by cervical dislocation at the endpoint.

2.11 Quantification of virus in infected lungs from mice

Lungs were harvested from mice 3 days post-infection. Following harvest, lungs were weighed, and then homogenized in sterile DMEM with gentamycin to generate a 20% lung-in-medium solution. Total RNA was extracted from lung homogenates using the ExtractRNA Reagent (Eurogen, Moscow, Russia) following the manufacturer’s instructions. Amplification and quantification of influenza A virus RNA were carried out by using a one-step RT-qPCR technique. To perform one-step RT-qPCR was used the reaction mixture containing (for one reaction) 5 pmol of each primer, 3 pmol of probe, 12.5 μl of 2xBioMaster RT-PCR-RT (Biolabmix, Moscow, Russia) and 10 μl of RNA (0.5 μg). The total volume of the one reaction mixture was 25 μl. The primers and probes were designed to target the gene coding M (matrix protein) of influenza A virus, the oligonucleotides were as follows: forward primer – 5’- ATG GAG TGG CTA AAG ACA AGA C -3’, reverse primer - 5’- GCA TTT TGG ACA AAG CGT CTA -3’, probe 5’-FAM - TCC TCG CTC ACT GGG CAC GGT -BHQ1-3’. Amplification was performed using a Real-time CFX96 Touch instrument (Bio-Rad, USA). The conditions of the one-step RT-qPCR reaction were as follows: 50°C for 15 min, 95°C for 5 min, followed by 45 cycles of 95°C for 10 s and 55°C for 1 min. The number of copies of viral RNA was calculated using a standard curve generated by amplification of a plasmid cloned DNA template containing the amplified fragment.

2.12 Statistical analysis

Data were analyzed using GraphPad Prism software version 9.5.0. Data of immunogenicity were analyzed using a Kruskal-Wallys test with Dunn’s multiple comparison test for inter-group analysis and Friedman test with Dunn’s comparison test for intra-group analysis of HAI titers through the time. Survival data were compared using the Mantel-Cox long-rank test with Dunn’s multiple comparison test and weight loss was compared using Tukey’s multiple comparison test. The viral load data were compared using Mann-Whitney test.

3.1 Preparation and characterization of mRNA vaccine compositions

To develop the vaccine, HAs of three influenza viruses were chosen: A/Wisconsin/588/2019 (H1), A/Darwin/6/2021 (H3), B/Austria/1359417/2021 (IBV, Victoria lineage). These strains of influenza virus were included in the WHO recommendations for the 2022-2023 seasonal influenza vaccine in the northern hemisphere ( 28 ). Codon optimized DNA sequences of HA genes were synthesized and cloned into the pJAZZ-OK linear bacterial plasmid, as described previously ( 21 ). In vitro synthesized mRNAs (schematically shown in Figure 1 ) included the cap-1 structure at the 5′ end; a 100-nt long poly(A)-tail at the 3′ end; the 5′ and 3′ untranslated regions (UTRs) from the human hemoglobin alpha subunit (HBA1) mRNA; and codon optimized coding sequences (CDS).

Figure 1 Design of mRNA-LNP for effective production of HA antigens in mammalian cells. (A) Scheme of mRNA with key parts, including 5’ and 3’ UTRs, influenza virus (IV) HA CDS, and poly(A)-tail; (B) Schematic visualization of separately formulated mRNAs encoding influenza HAs from three seasonal (2022-2023) vaccine strains.

N1-methylpseudouridines (m1Ψ) were co-transcriptionally incorporated into the mRNA instead of 100% uridines (U). mRNA-LNP formulations were prepared using the microfluidic NanoAssemblr Ignite mixer. The encapsulation efficiency was 89% (SD 1.2%) with a typical average particle size in the range of 68-71 nm with 0.105-0.148 polydispersity index ( Supplementary Table S1 ).

A proper expression of the in vitro synthesized mRNAs was confirmed by transfection of cultured human embryonic kidney cells (HEK293) followed by their immunocytochemical staining for the H1N1 HA product. The presence of the HA protein (H1N1 A/Wisconsin/588/2019) was detected both inside the cells (intracellular staining, Figures 2A, C ) and in the membrane-associated form (surface cell staining, Figures 2B, D ).

Figure 2 In vitro expression of hemagglutinin (H1N1 A/Wisconsin/588/2019) in HEK293 cells transfected with synthetic mRNA. (A, B) – mRNA-transfected HEK293 cells were immunostained for intracellular or surface HA protein respectively. (C, D) – the same staining of untransfected HEK293 cells (C) – intracellular, (D) – surface). Immunostaining was performed using primary polyclonal anti-Influenza A Antibody and Donkey Anti-Goat IgG H&L (Alexa Fluor ® 488) secondary Ab (green), nuclei were stained with DAPI (blue). Scale bar 100 µm.

These results confirmed the translational activity of our synthetic mRNAs in cultured cells. In particular, the presence of the HA antigen on the cell surface indicated the correct design of the mRNA coding part containing a region for the HA transmembrane domain, which ensures the anchoring of the antigen to the host cell membrane.

3.2 Immunogenicity of two doses of the multivalent HA-mRNA vaccine

Immunogenicity of prepared mRNAs were investigated in mice using HAI assay, as described previously ( 29 ). Initially, we tested the immunogenicity of H1 and H3 HA-encoding mRNAs separately ( Supplementary Figure S1 ). HAI titers were measured after two 10-mg doses of individually formulated either H1 or H3 mRNA were administrated to BALB/c mice (n=6) intramuscularly (IM). HAI titers were up to 1:1280 above baseline by day 7 after second dose.

Next, to determine the immunogenicity of combined mRNA influenza vaccine candidate (mRNA-IV), HAI titers were determined in BALB/c mice (n=3) after two dose immunization with 15 µg of an equimolar mixture of individually formulated H1, H3, and IBV mRNA-LNPs ( Figure 3A ). Thus, one dose of mRNA-IV contains 5 µg of each mRNA. This dose was selected as a potential 1/10 human dose of mRNA, by analogy with vaccines for the prevention of COVID-19. One control group of mice (n=3) received 6 µg (1/10 human dose) of split inactivated influenza vaccine (SIIV), another control group (n=3) received equal volume of sterile PBS. The SIIV contained 4 antigens according to WHO recommendations for the 2022-2023 seasonal influenza vaccine in the northern hemisphere ( 28 ). The second dose was administered IM 14 days after the first dose.

Figure 3 Mice immunized with mRNA-IV generate robust antibody responses. BALB/c mice (n=3 per group) were vaccinated intramuscularly at week 0 and 2 with a mixture of three different HA-mRNA-LNPs (a combined total dose of 15 µg mRNA per mouse (n=3), including 5 µg of each individual HA-mRNA-LNP). Control BALB/c mice were immunized intramuscularly with 1/10 human dose of quadrivalent split inactivated influenza vaccine (SIIV, a combined total dose of 6 µg per mouse, including 1.5 µg of each individual antigen), and another control BALB/c mice were administered PBS intramuscularly. (A) The scheme of the animal experiment. Serum HAI titers were determined after 7, 21, and 35 days post prime dose (V1) with antigens of vaccine strains: (B) H1N1 A/Wisconsin/588/2019, (C) – H3N2 A/Darwin/9/2021, (D) – B/Austria/1359417/2021. Group mRNA-IV shown in green, SIIV – in violet, and PBS – in blue. Data are representative of one experiment and shown as geometric means ± SD. Data were analyzed using a Kruskal-Wallys test with Dunn’s multiple comparison test for inter-group analysis and Friedman test with Dunn’s comparison test for intra-group analysis of HAI titers through the time.

3.2.1 H1 vaccine component

Analysis of the immune response to the H1 component of the mRNA vaccine showed high HAI titers against the homologous strain A/Wisconsin/588/2019 with geometric mean of 1:3413 (7 days after the second dose of vaccine). Compared to the control split vaccine (SIIV), the mRNA-LNP showed a rapid immune response significantly exceeding the limit of detection (LOD) as early as a week after the first vaccine dose. The average HAI titer against the A/Wisconsin/588/2019 antigen for the mRNA group after first dose was 1:126; for the SIIV group it was below the LOD (Mann-Whitney test p=0.1 , Figure 3B ). However, the Wilcoxon rank test showed no significant differences. On the 7th day after second vaccination, the differences in the level of antibody response in mRNA and split vaccine groups are especially noticeable - 1:3225 and 1:40, respectively (80-fold differences), however, due to the small sample size, significant differences between these groups could not be found. Also, if we consider changes in the level of immune response within the group over time (on days 7, 21, and 35 after V1), a significant increase in the immune response is noted for the mRNA group after the second vaccine dose. For the mRNA group HAI titers against H1N1 on day 21 after V1 significantly exceed those on day 7 after V1 ( p=0.0429 , Friedman multiple comparison test). A decrease in antibody response by day 35 after V1 compared to day 21 was statistically not significant (Wilcoxon test p=0.25 ), the mean HAI titers differ by 2.2 times ( Figure 3B ). These differences are within the error of the HAI method, since the serum dilution factor in the study was equal to 2. A similar comparison in the SIIV group also did not reveal significant differences in HAI titers between 21 and 35 days against the A/Wisconsin/588/2019 strain ( p=0.75 ). This may be due to the small sample size.

3.2.2 H3 vaccine component

For the H3 component of the vaccines, we obtained a similar immunological profile, but with more pronounced differences between mRNA and split vaccine in terms of the level of immune response ( Figure 3C ). As we did not have the influenza vaccine strain A/Darwin/9/2021 in our virus strain collection, HAI titers were determined using the antigen of serologically close strain A/Darwin/6/2021 (2 amino acids substitutions in HA protein sequence - G69D, D202N). Thus, H3-mRNA (A/Darwin/9/2021), in trivalent mRNA-IV vaccine caused a detectable antibody response already on day 7 after V1 (mean 1:23), while for split vaccine this value was below the LOD ( Figure 3C ). Seven days after the second vaccination, the mean titer of HAI in the mRNA group reaches 1:2987, while in sera from mice that received the split inactivated vaccine, this value remains below the LOD ( Figure 3C ). Increase of HAI titer in serum of mice vaccinated by SIIV was observed only to 35 days after V1, however it remains 86-fold lower than this value for the mRNA vaccine (mean HAI titer in mRNA vaccinated mice - 1:1387). When comparing immunogenicity through the time of experiment (7, 21, and 35 days after V1) within the mRNA group, there was observed significant increase after the second dose of mRNA on day 21 (with a mean titer of 1:2987), in comparison with serum titers on day 7 ( p=0.0429 , Friedman multiple comparison test). There were no significant differences in titers between days 21 and 35 ( p=0.66 ).

3.2.3 B (Victoria) vaccine component

The immune response in vaccinated mice to influenza B virus (Victoria lineage) was lower compared to two previous vaccine components (H1 and H3). Two-dose vaccination with mRNA-LNP resulted in lower serum HAI titers to B/Austria/1359417/2021 antigens than to H1N1 antigens (mean HAI titer in mRNA vaccinated mice – 1:960 at 21 days post V1, Figure 3D ). However, just 7 days after the first dose, HAI titers for the mRNA group exceeded the LOD (mean HAI titer - 1:45), while in the split vaccine group, the mean HAI titer was below the LOD (mean HAI titer - 1:5). The difference in the level of immune response to mRNA and split vaccines is much less for the B component of the vaccine than for the H1 and H3 components. A decrease in antibody response by day 35 after V1 compared to day 21 was not statistically significant ( p=0.25 , Wilcoxon test).

3.2.4 Cross-reactivity of immune response 3 weeks after two-dose vaccination

On day 35 after the start of the experiment, the whole blood was collected from the mice for more in-depth studies. This allowed us to study the cross-reactivity of the immune response after the vaccination to more than one different influenza strain only for endpoint serum sample of mice (21 days post second dose, Figure 4 ). For the H1N1 strains we used (Wisconsin/588/2019, Victoria/2570/2021, Guangdong-Maonan/SWL1536/2019, Moscow/52/2022, California/07/2009), the immune response is highly cross-reactive in the group of mRNA-vaccinated animals. The geometric mean HAI titers against H1N1 strains were from 1:806 (against Guangdong-Maonan/SWL1536/2019 antigen) to 1:2032 ( Figure 4A ).

Figure 4 Mice immunized with mRNA-IV generate cross-reactive antibody responses. BALB/c mice (n=3 per group) were vaccinated intramuscularly at week 0 and 2 with 3 different HA mRNA-LNPs (a combined total dose of 15 µg per mouse (n=3), including 5 µg of each individual HA mRNA-LNP). Control BALB/c mice were immunized intramuscularly with 1/10 human dose of registered quadrivalent split inactivated influenza vaccine (SIIV, a combined total dose of 6 µg per mouse, containing 1.5 µg of each individual antigen), and another control BALB/c mice were administered PBS intramuscularly. Serum titers in heterologic HAI were determined after 35 days post prime dose with antigens of different influenza strains: (A) strains of H1N1 influenza subtype (Wisconsin/588/2019, Guangdong-Maonan/SWL1536/2019, Moscow/52/2022, California/07/2009), (B) – strains of H3N2 influenza subtype (Darwin/9/2021, Perth/165/2009, Kansas/14/2017), (C) – strains of influenza B (Victoria lineage – Austria/1359417/2021, Washington/02/2019, Colorado/06/2017, Brisbane/60/2008). Group mRNA-IV shown in green, SIIV - in violet and PBS - in blue. Data are representative of one experiment and are expressed as geometric means ± SD.

There was no significant reduction in HAI titers even to distant pandemic A/California/07/2009 strain with mean value 1:1015 ( Figure 4A ). The immune response to SIIV was not as robust as to mRNA-IV, the mean titer value did not exceed 1:31 (against Victoria/2570/2021 antigen), which more than 60-fold lower comparing with mRNA. For single H1-mRNA study of cross-reactivity of immune response showed similar results ( Supplementary Figure S2 ).

The cross-reactivity of immune response to H3 component ( Figure 4B ) of the vaccine was manifested by decreased titers to the Kansas/14/2017 strain (the geometric mean HAI titer was 1:63) and no detectable response to the Perth/165/2009 strain, while response to serologically close strain A/Darwin/6/2021 remained to be high with geometric mean HAI titer 1:1015.

Noticeable results were obtained in a heterologous HAI test with the antigens of influenza virus B strains (B/Washington/02/2019, Colorado/06/2017 and Brisbane/60/2008, Figure 3C ). Immune response against listed strains was reduced compared to homologous HAI results ( Figure 3C ) for both mRNA and split inactivated vaccine. In the mRNA group, the decrease in mean HAI titers to the Washington/02/2019 antigen was 12-fold and to the Brisbane/60/2008 antigen was 8-fold. No immune response to the Colorado/06/2017 antigen was detected in the serum of mice vaccinated with both mRNA and SIIV. In the SIIV group, no immune response to the Washington/02/2019 antigen was detected and the reduction in HAI titers to Brisbane/60/2008 compared to homologous was more than 5-fold.

We tested the hypothesis that the cross-reactivity of the immune response of mice after immunization with an mRNA vaccine is due to the high content of antibodies specific to the conservative domains of hemagglutinin by examining the sera of immunized mice in ELISA. The study involved sera received from mice (n=6 per group) 35 days post vaccination with trivalent mRNA, SIIV and PBS according to the previously described scheme ( Figure 3A ). ELISA analysis of sera was carried out with two antigens – a modified trimeric HA stem domain (influenza H1N1 A/Brisbane/59/2007) ( 27 ) and the HA head domain (HA1 subunit of influenza A H1N1 A/California/04/2009). Results of ELISAs demonstrated high antibody level against both HA subunits in mRNA vaccinated mice’s serum in comparison with ones vaccinated with SIIV ( Figures 5A–D ). Geometric mean of area under curve for mRNA group significantly differ from these values for PBS and SIIV groups in ELISA with both HA subunits ( Figures 5B, D ). The serum end-point titers, calculated based on ELISA data showed 100-fold and 1000-fold increase in antibody levels in mice vaccinated with mRNA compared to SIIV against HA head domain and HA stem domain respectively ( Supplementary Figures 3B, D ).

Figure 5 Antibody levels measured by ELISA to HA subunits of distant influenza A strains as possible explanation of cross-reactive immune response to the trivalent mRNA vaccination. Mice were twice vaccinated by trivalent mRNA, including 5 µg of each individual HA mRNA-LNP, or 1/10 human dose of SIIV, or PBS as earlier described. (A, C) Representative ELISA curves of antibody levels to HA head (HA1 subunit of influenza A H1N1 A/California/04/2009) and stem (modified trimeric HA2 influenza H1N1 A/Brisbane/59/2007) domains respectively. (B, D) The same data are represented as geometric means of area under ELISA curves and compared by Mann-Whitney test.

3.3 Protective efficacy of two doses of the trivalent HA-mRNA vaccine

In order to evaluate the effectiveness of immunity formed by mRNA-LNP vaccination, we conducted an experiment using an animal model of lethal influenza infection. This model included infection of BALB/c mice vaccinated according to the chosen regimen with mouse-adapted influenza A/Victoria/2570/2019 virus. The design of the experiment is shown in Figure 6A .

Animals immunized with PBS (n=13) and animals that received 1/10 human dose of inactivated split vaccine were used as comparison groups. Fourteen days after second immunization according to the scheme in Figure 6A mice were infected intranasally with 25 LD 50 of H1N1 pdm09 virus (A/Victoria/2570/2019, mouse adapted), which had 99.8% HA amino acid homology to the H1 component of the mRNA vaccine. On the third day after infection, 3 mice from each group were euthanized for lung isolation. Viral load was assessed in lung homogenates by RT-PCR with normalization to a housekeeping gene, PDK1 (encoding pyruvate dehydrogenase kinase-1). In the mRNA vaccinated mice group, the average viral load in the lungs was 3.5 copies/mL, while in the PBS and SIIV control groups, the mean Log10 viral load was 6.65 and 6.4 genome copies/mL, respectively ( Figure 6B ). The viral load in the lungs of mRNA vaccinated mice was almost undetectable in contrast to the PBS and SIIV control groups ( p<0.0001 and p=0.0382 , respectively, Figure 6B ). On day 6 post-infection, 46% of the animals in the control group died and all animals died on day 9 ( Figure 6C ). In the group of animals that received the inactivated split vaccine, the lethality rate on (or between) days 7–9 of infection was 23%. No animal deaths were observed in the group that received the mRNA-IV. Both vaccines protected animals from 25 LD 50 doses of virus with statistical reliability ( p<0.0001 compared to the PBS group). No significant differences were found between vaccines according to these statistical tests. Evaluation of weight dynamics shows that animals from the control group started active weight loss from the second day after infection ( Figure 6D ). In the group of animals receiving SIIV, weight loss was observed until the 3rd day of infection with subsequent recovery. No weight loss was observed in the group of animals receiving mRNA. On day 1 after infection, an average increase in body weight of 3% was observed for animals in the SIIV group and the value of this parameter was significantly higher than that of the mRNA-IV group. However, from day 2 post-infection until the end of observations (day 10), weight loss was minimal for the mRNA-IV group and was significantly lower for the other two groups of mice that received inactivated vaccine or PBS ( Figure 6D ).

Figure 6 The mRNA-IV vaccine protects mice from influenza infection with antigenically close H1N1 strain. BALB/c mice were immunized with two-dose of mRNA vaccine and challenged with 25 LD 50 of H1N1 virus (A/Victoria/2570/2019, mouse adapted). (A) The scheme of challenge experiment. At third day post infection lungs of mice (n=3) from every group were harvested and analyzed by qPCR for viral load determination (B) . Survival (C) and weight loss (D) of the remaining animals were recorded post challenge. Data are representative of one experiment and shown as geometric means ± SD. Data were compared using a Long-rank (Mantel-Cox) test with Dunn’s multiple comparison test for survival analysis and Tukey’s multiple comparisons test for analysis of weight loss differences between groups. The viral load data were compared using Mann-Whitney test. P-value shown as asterisks, *p< 0.05, **p< 0.01, ***p< 0.001, ****p< 0.0001 .

4 Discussion

Due to the ongoing genetic perturbations and evolution of influenza viruses, including antigenic drift ( 30 ) and recombination ( 31 , 32 ), the antigenic characteristics of the pathogen undergo continuous changes. As a result, the immunity generated by previous exposure or vaccination becomes less effective. This continually puts the human population at risk of seasonal influenza epidemics. To address this challenge, the WHO Global Influenza Surveillance and Response System (GISRS) monitors influenza viruses circulating in humans and updates the antigenic composition of vaccines twice a year (for the southern and northern hemispheres) ( 33 ). Manufacturers of influenza vaccines receive guidance on the specific antigenic composition, including two serologic variants of influenza A and two serologic variants of influenza B, to be incorporated in vaccines for the upcoming season ( 34 ). However, mistakes in the strain selection, as well as the need to enhance protection in vulnerable groups, have prompted the search for novel approaches to develop influenza vaccines that offer broader and more effective protection ( 35 , 36 ).

The mRNA platforms hold significant promise for the development of influenza vaccines and offer several advantages. First, it enables rapid vaccine creation and production in event of a completely new virus strain, allowing for a timelier response to emerging threats ( 37 ). Second, unlike traditional methods, mRNA vaccine production does not require the use of live virus and can be based on synthetic sequences obtained in the laboratory. This eliminates the risk of unintended mutations that may arise from virus passages. Third, mRNA-based vaccines are highly precise in targeting the immune response as they express only specific antigens, such as influenza HA ( 38 ). Finally, the delivery of mRNA formulated in LNPs not only promotes both humoral and cellular immune responses but also activates the innate immune system, further enhancing the effectiveness of the vaccine ( 39 ).

In our work, we present the results of creating a candidate mRNA vaccine with an antigen composition recommended by the WHO for use in seasonal vaccines in the northern hemisphere in 2022-2023: A/Wisconsin/588/2019 (H1), A/Darwin/6/2021 (H3), and B/Austria/1359417/2021 (IBV, Victoria lineage) ( 28 ). We hypothesized that the cross-reactivity of the immune response toward heterologous strains of the influenza virus can be obtained due to the features of mRNA vaccine platform. The viral antigen is synthesized directly in the cells of the immunized organism, with a natural folding and glycosylation pattern. It undergoes processing in proteasomes and is displayed by MHC class I proteins. Additionally, antigens that are secreted can be taken up by cells, degraded inside endosomes, and presented on the cell surface to helper T cells by MHC class II proteins ( 37 ). We used a quadrivalent inactivated split vaccine as a control, which also has the recommended antigen composition. In the main series of experiments, we used vaccines at 1/10 of the human dose (set in the case of split vaccine and assumed for the mRNA vaccine) to allow comparison of platforms when assessing immunogenicity in mice. Both vaccines showed detected immunogenicity using the HAI method. This method is the gold standard for assessing the immunogenicity of influenza vaccines and the efficacy of immunity against novel virus variants ( 29 ).

The level of humoral response in HAI to the mRNA vaccine injection was on average 10-100 times higher than that to the split inactivated vaccine for all subtypes. This correlates with previously obtained data for the combined mRNA vaccine ( 40 ). When immunogenicity was analyzed by ELISA method (against H1N1pdm) for the group of mice immunized with the combined mRNA vaccine, as well as in our case, 10-100 times higher levels of antibodies (depending on the dose of mRNA) were observed compared to this value in the group of animals vaccinated with quadrivalent inactivated vaccine (at a dose of 1.5 µg). The levels of antibody response for the inactivated vaccine obtained in our experiments were in good agreement with the data of the cell-based split vaccine study ( 41 ). For a 1.5 μg dose of each antigen separately, HAI titers comparable to those obtained in our work for the quadrivalent vaccine were obtained (HAI titers to H1N1 averaged about 1:90, to H3N2 averaged about 1:500, and to B (Victoria lineage) averaged about 1:30). One could speculate that this difference between the immune response to the mRNA and the split vaccine could be due to the dose of antigen delivered. Thus, in the case of the inactivated vaccine, the dose of individual antigens was 1.5 μg, whereas for the mRNA composite, the dose of each antigen was 5 μg. Unfortunately, there is no adequate method to quantitatively compare antigen delivered using different vaccine platforms. Delivery of the antigenic protein and its analogue in mRNA form initially yields different pharmacokinetics. According to one of the studies, based on the results of an in vitro experiment, 1 pmol of the spike protein was obtained using 6 pmol of mRNA vaccine for 24 hours during transfection of BHK cell culture ( 42 ). According to our earlier experiments, when we delivered 10 μg of mRNA (approximately 20 pmol) encoding the B11 antibody against botulinum toxin we achieved a maximum antibody concentration in mouse serum of 99 ng/mL, which translates to about 2.35 pmol of antibody per average serum volume of an 18-g mouse ( 21 ). Both examples indicate that the amount of antigen produced with the target mRNA is 5-10 times less compared to the amount of mRNA used. Thus, it is more likely that the advantage of mRNA in the context of the generated humoral response is not due to the obviously higher concentration of antigen achieved by the selected dos-es, but is due to a complex of differences including the mRNA platform itself compared to the delivery of purified antigens used in split vaccines.

As a result of the protective efficacy study using 25 LD 50 of H1N1 virus (A/Victoria/2570/2019, mouse adapted), we demonstrated the protective effect of both mRNA and split vaccine compositions. In the case of mRNA, no animal deaths were registered during the observation period, whereas in the group of mice that received split vaccine, 3 out of 10 animals died. These data correlated with the dynamics of weight of infected animals (for split vaccine, weight loss was observed from days 3 to 9 of observation), as well as viral load in the lungs - on day 3, the difference in viral load between the groups that received mRNA composition and split vaccine was 10 6 . We were unable to find studies that examined the protectiveness of mRNA and split vaccines in a single animal experiment, but there are studies of split vaccine candidates produced by virus production in the MDCK cell line ( 41 ). On day 4 after 10 7 cell culture infectious dose 50% (CCID 50 ) infection with H1N1 influenza virus, a weight loss of up to 10% was observed in the group of mice vaccinated with 5 μg split mono-vaccine, and the amount of virus in the lungs of infected mice isolated on day 6 was 10 2 virus copies/mL, compared with 10 5 virus copies/mL in the placebo group. This is indicative that both in our case and in the Zhang et al. study, influenza virus was detected by qPCR in the lungs of animals vaccinated with inactivated split vaccines after infection. In our study, in the mRNA group, the viral load in the lungs was below the detection limit, which is consistent with the data obtained by Arevalo et al. for both 20-valent and monovalent H1-mRNA influenza vaccines ( 16 ). In the lungs of control mice immunized with mRNA vector with luciferase (placebo), the viral load determined by median tissue culture infectious dose 50% (TCID 50 ) assay was approximately 5×10 4 TCID 50 /mL, and in groups of mice immunized with mono H1-mRNA preparation or 20-valent mRNA, the viral load was below the detection limit. As for the results of animal death in the split vaccine group (n = 3), this effect was observed by researchers of adjuvants for influenza vaccines ( 43 ). When intranasally administering a split vaccine, they observed 100% mortality of animals by day 6 after infection with 10 LD 50 adapted to mice influenza virus A H1N1 A/California/04/2009. On the 3rd day after infection, the virus titer in the bronchoalveolar lavage of infected mice was 6.7 ± 0.1 Log10 PFU/mL. In general, the death of mice immunized with split influenza vaccines after infection with different doses of influenza viruses is not a new phenomenon. It has been noted in other studies as well ( 43 , 44 ). Our results for the split-vaccine in terms of the efficacy of protecting vaccinated mice from death are consistent with the published data. However, for preclinical studies of influenza vaccine efficacy, ferrets are the preferred animal model ( 45 ).

As a result of using heterologous to the vaccine influenza virus antigens in the HAI test, we demonstrated a broader serum hemagglutinating activity in mice receiving the mRNA composition compared to those receiving the split inactivated influenza vaccine. The immune response to the B/Washington/02/219 strain, which was heterologous to the vaccine strain, was at a level exceeding the lower limit of detection and increased after repeated vaccination. However, in the group of animals immunized with the split vaccine, serum HAI titers were below the LOD at all-time points, and no enhancement of immunity by repeated vaccination was observed. The findings indicate a higher potential for the formation of a cross-specific humoral immune response by mRNA compositions. An extended study with four different H1N1 antigens confirmed the findings. Statistically significant differences in serum activity against evolutionarily more distant virus variants (A/California/07/2009pmd, A/Guangdong-Maonan/SWL1536/2019), especially on day 14 after immunization, were detected. However, on day 39, the sera showed high activity against all variants; differences in the level of immune response in hetero- and homologous HAI titers were statistically insignificant, and average serum titers ranged from 1:160 (in the case of the most distant A/California/07/2009pdm) to 1:1280 (in the case of the epidemic strain A/Moscow/52/22, which circulated in the epidemic season 2022–23 after the vaccine was released). These data correlate with the results of previously published works, which demonstrated the presence of binding and neutralizing antibodies against the H1N1 strain (A/Michigan/45/2015, distant to the vaccine) in the monovalent mRNA vaccine. However, a two-fold reduction in the binding level and the absence of neutralizing antibodies were observed against the second, more distant H1N1 strain, A/Puerto-Rico/08/1934 [16]. We have demonstrated the cross-immunity due to mRNA vaccination against a strain that emerged after updating the vaccine composition for the 2022-2023 season, acquiring 9 substitutions in the amino acid sequence of HA (relative to A/Wisconsin/588/2019). It is important to note that cross-reactivity of the immune response to mRNA vaccine is achieved by the presence of HA mRNA from one strain of influenza subtype in the vaccine.

We hypothesized that the cross-reactivity of the immune response after immunization with an mRNA vaccine is due to the higher content of antibodies specific to the conservative domains of hemagglutinin. Our hypothesis was supported by our results of antibody levels estimation to HA stem domain. The serum end-point titers were 1000-fold higher in mice vaccinated with mRNA compared to SIIV. A recombinant modified trimeric HA stem domain (#4900) has well known as broadly protective immunogen ( 46 ) and due to modifications, it has low identity in amino acid sequence with the stem domain of mRNA coding HA and HA from SIIV (78.9% both). As for the head HA subunit serum end-point titers was a 100-fold higher in mice vaccinated with mRNA compared to SIIV. It can additionally provide quantitative and qualitative advantage increasing cross-reactivity of the immune response. It is known, that head domain of HA has some conservative regions, which are have been showed to be a target for broad neutralizing antibodies ( 47 – 49 ). Thus, our results suggest that the nature of the broader immune response may be due to qualitative and quantitative advantages of antibodies generated by mRNA vaccines compared to split vaccines. In turn, this may be related to the ability of the platform mRNA to provide the natural folding and glycosylation pattern of the antigen.

In summary, the results presented in this study highlight the potential of mRNA-based platforms for the development of influenza vaccines and suggest the need for further research in this area. To fully understand the universality, breadth, and effectiveness of the immune response elicited by mRNA vaccines, it is crucial to conduct additional studies evaluating the immunogenicity and protective efficacy against more diverse strains of H1, H3, and BV in vivo . It is also important to validate the data obtained from hemagglutination tests by conducting sera microneutralization assays. Additionally, including a group of mice immunized with non-lethal doses of live virus as a positive control in immunogenicity studies can provide valuable insights into the models of the natural immunity. These findings hold significant implications for the development of mRNA vaccines that offer broader protection against a wide range of influenza strains.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics statement

The animal study was approved by The Institutional Animal Care and Use Committee (IACUC) of the Federal Research Centre of Epidemiology and Microbiology named after Honorary Academician N.F. Gamaleya. The study was conducted in accordance with the local legislation and institutional requirements.

Author contributions

EPM: Writing – original draft, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. VG: Writing – original draft, Supervision, Project administration, Investigation, Conceptualization. DK: Writing – review & editing, Investigation. AS: Writing – review & editing, Methodology, Investigation. EIB: Writing – review & editing, Supervision, Methodology. MS: Writing – review & editing, Resources, Investigation. EAM: Writing – review & editing, Investigation, Formal analysis. ENB: Writing – review & editing, Investigation. SK: Writing – review & editing, Investigation, Formal analysis. EE: Writing – review & editing, Resources, Investigation. AZ: Writing – review & editing, Investigation. ES: Writing – review & editing, Investigation. EK: Writing – review & editing, Investigation. AK: Writing – review & editing, Investigation. EU: Writing – review & editing, Investigation. NK: Writing – review & editing, Investigation. II: Writing – review & editing, Resources, Investigation. SD: Writing – review & editing. RI: Writing – review & editing. DL: Writing – review & editing, Supervision, Investigation. AG: Writing – review & editing, Supervision.

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This research was funded by National Research Centre for Epidemiology and Microbiology named after Honorary Academician N F Gamaleya (from the income-generating activities) and the grant #121102500071-6 provided by the Ministry of Health of the Russian Federation, Russia.

Acknowledgments

We are grateful to Dr. Dmitry V. Shcheblyakov and Daria V. Voronina from the laboratory of immunobiotechnology of the National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N. F. Gamaleya for providing ELISA proteins.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fimmu.2024.1381508/full#supplementary-material

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Keywords: seasonal influenza, vaccine, mRNA, immunogenicity, efficacy, immune response

Citation: Mazunina EP, Gushchin VA, Kleymenov DA, Siniavin AE, Burtseva EI, Shmarov MM, Mukasheva EA, Bykonia EN, Kozlova SR, Evgrafova EA, Zolotar AN, Shidlovskaya EV, Kirillova ES, Krepkaia AS, Usachev EV, Kuznetsova NA, Ivanov IA, Dmitriev SE, Ivanov RA, Logunov DY and Gintsburg AL (2024) Trivalent mRNA vaccine-candidate against seasonal flu with cross-specific humoral immune response. Front. Immunol. 15:1381508. doi: 10.3389/fimmu.2024.1381508

Received: 03 February 2024; Accepted: 29 March 2024; Published: 16 April 2024.

Reviewed by:

Copyright © 2024 Mazunina, Gushchin, Kleymenov, Siniavin, Burtseva, Shmarov, Mukasheva, Bykonia, Kozlova, Evgrafova, Zolotar, Shidlovskaya, Kirillova, Krepkaia, Usachev, Kuznetsova, Ivanov, Dmitriev, Ivanov, Logunov and Gintsburg. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Elena P. Mazunina, [email protected] ; Vladimir A. Gushchin, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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Monday, April 8, 2019

Scientists review influenza vaccine research progress and opportunities

In a new series of articles, experts in immunology, virology, epidemiology, and vaccine development detail efforts to improve seasonal influenza vaccines and ultimately develop a universal influenza vaccine. The 15 articles are part of a supplement in the April 15 issue of the Journal of Infectious Diseases . Researchers from the National Institute of Allergy and Infectious Diseases (NIAID), part of the National Institutes of Health, and scientists supported by NIAID, are among the contributing authors. Barney S. Graham, M.D., Ph.D., deputy director of NIAID’s Vaccine Research Center (VRC), and Michelle C. Crank, M.D., head of the Translational Sciences Core in the VRC’s Viral Pathogenesis Laboratory, edited the supplement.

In an introductory article, NIAID Director Anthony S. Fauci, M.D. and Catharine I. Paules, M.D., an infectious disease physician at Penn State Health Milton S. Hershey Medical Center, underscore the public health need for improved influenza vaccines, noting the approximately 291,000 to nearly 646,000 deaths worldwide each year due to seasonal influenza. They also discuss the possibility of another influenza pandemic, which occurs when a novel influenza virus to which most people do not have immunity arises unpredictably. The 1918 influenza pandemic caused an estimated 50 million to 100 million deaths.

The current seasonal influenza vaccine reduces influenza-related hospitalizations and deaths. However, people must get vaccinated annually due to constantly changing influenza viruses, and in some years, the vaccine confers less-than-optimal protection against infection. Drs. Fauci and Paules note that recent scientific advances, combined with scientists’ efforts to coordinate and accelerate their research activities, have provided unprecedented momentum toward developing a so-called “ universal” influenza vaccine . Such a vaccine would offer long-term protection against multiple seasonal and pandemic influenza viruses.

The supplement articles detail ongoing research and what remains to be learned about influenza—such as how the human immune system responds to influenza infection and vaccination. Experts also discuss how such research might influence vaccine design approaches and help the public health community better prepare for the next influenza pandemic.

In closing remarks, Drs. Crank and Graham, along with John R. Mascola, M.D., VRC director, note, “Vaccinology is experiencing a revolution thanks to scientific and technological breakthroughs of the past decade, and hopefully we can find the resolve, political will, and new business plans to take full advantage of these new opportunities and prepare ourselves before the next pandemic arrives.”

Articles in the supplement from NIAID experts include:

CI Paules and AS Fauci. Influenza vaccines: good, but we can do better. Journal of Infectious Diseases DOI: 10.1093/infdis/jiy633 (2019)

CM Saad-Roy et al . Dynamic perspectives on the search for a universal influenza vaccine. Journal of Infectious Diseases DOI: 10.1093/infdis/jiz044 (2019)

DM Morens and JK Taubenberger. Making universal influenza vaccines: lessons from the 1918 pandemic. Journal of Infectious Diseases DOI: 10.1093/infdis/jiy728 (2019)

MC Crank et al . Preparing for the next influenza pandemic: the development of a universal influenza vaccine. Journal of Infectious Diseases DOI: 10.1093/infdis/jiz043 (2019)

M Kanekiyo et al . New vaccine design and delivery technologies. Journal of Infectious Diseases DOI: 10.1093/infdis/jiy745 (2019)

NIAID Director Anthony S. Fauci, M.D., is available for comment.

To schedule interviews, please contact Jennifer Routh, (301) 402-1663, [email protected] .

NIAID conducts and supports research — at NIH, throughout the United States, and worldwide — to study the causes of infectious and immune-mediated diseases, and to develop better means of preventing, diagnosing and treating these illnesses. News releases, fact sheets and other NIAID-related materials are available on the NIAID website .

About the National Institutes of Health (NIH): NIH, the nation's medical research agency, includes 27 Institutes and Centers and is a component of the U.S. Department of Health and Human Services. NIH is the primary federal agency conducting and supporting basic, clinical, and translational medical research, and is investigating the causes, treatments, and cures for both common and rare diseases. For more information about NIH and its programs, visit www.nih.gov .

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Research finds flu vaccines were effective in 2022–2023 flu season

by Regenstrief Institute

The prospect of the worrisome triple threat of COVID, RSV, and flu was assuaged last year by the effectiveness of flu vaccines. Two recent studies from the Centers for Disease Control and Prevention's VISION Network have found that flu vaccines were effective for all ages against both moderate and severe flu in the U.S. during the 2022-2023 flu season.

Both the pediatric and adult VISION Network studies analyzed flu-associated emergency department (E.D.)/urgent care visits (indicative of moderate disease) and hospitalization (indicative of severe disease) from October 2022 through March 2023, a flu season in which far fewer individuals were social distancing or wearing masks than during the two previous flu seasons.

Vaccination reduced the risk of flu-related E.D./urgent care visits and hospitalization for those 6 months to 17 years by almost half. For adults, regardless of age, vaccination reduced the risk of E.D. urgent care visits by almost half and reduced the risk of hospitalization by slightly more than a third.

These results led the authors of both studies to conclude that flu vaccination is likely to substantially reduce illness, death, and strain on health care resources.

"We study the effectiveness of flu and other vaccines to ensure that our processes for forecasting the most effective vaccines are working well and therefore might potentially also be translatable to other diseases as well," said Shaun Grannis, M.D., M.S., a co-author of both the pediatric and adult VISION Network studies, Regenstrief Institute vice president for data and analytics and a family practice physician.

"Given influenza's significant disease burden—for example, the H1N1 (swine) flu killed over a quarter of a million people worldwide in 2009-2010—we want to make sure that we understand virus trends as well as other factors and that we're continuing to do as well as and as much as we can to reduce the flu disease burden."

Both the pediatric and adult studies evaluated electronic health record (EHR) data from sites across three health care systems in California, Utah, Minnesota, and Wisconsin.

Flu vaccine effectiveness: 2022-2023 flu season for ages 6 months to 17 years

Vaccination reduced the risk of flu-related E.D./urgent care visits (moderate disease) by 48 percent and hospitalization (severe disease) by 40 percent overall across ages 6 months to 17 years. Broken down by age, risk reduction was greater for those aged 6 months to 4 years than for older children and adolescents.

Ages 6 months to four years

• Vaccination reduced the risk of E.D./urgent care visits (moderate disease) by 53 percent.
• Vaccination reduced the risk of hospitalization (severe disease) by 56 percent.

Ages 5 to 17 years

• Vaccination reduced the risk of E.D./ urgent care visits (moderate disease) by 38 percent.
• Vaccination reduced the risk of hospitalization by 46 percent.

Approximately 30 percent of E.D./critical care visits for acute respiratory illness in children and adolescents were positive for flu, as were 14 percent of hospitalizations.

" Vaccine Effectiveness Against Pediatric Influenza-A-Associated Urgent Care, Emergency Department, and Hospital Encounters During the 2022-2023 Season, VISION Network " is published in Clinical Infectious Diseases .

Flu vaccine effectiveness: 2022-2023 flu season for ages 18-64

Vaccine effectiveness was 45 percent against E.D./critical care visits(moderate disease) for adults under age 65. Effectiveness against hospitalization (severe disease) was 23 percent.

Adults younger than 65 typically received standard-dose inactivated vaccines.

Flu vaccine effectiveness: 2022-2023 flu season for ages 65 and older

Vaccine effectiveness was 41 percent against both flu-associated E.D./urgent care visits (moderate disease) and hospitalization (serious disease) for this age group.

Adults age 65 and older typically received enhanced vaccine products.

" Influenza vaccine effectiveness against influenza-A-associated emergency department, urgent care, and hospitalization encounters among U.S. adults, 2022-2023 " is published in the Journal of Infectious Diseases.

"As with COVID, the dynamics of flu differs between children and adults. But we found that for both children and adults, vaccination significantly reduced the need for trips to the E.D. or critical care center and for hospitalization for flu-related illnesses last flu season, and this is encouraging," said Dr. Grannis.

"I'm hopeful that we will see similar or even better vaccine effectiveness during the current flu season. Even if they do experience symptoms, people who are vaccinated typically tend to have milder, shorter cases of the flu, a viral illness which can carry a severe disease burden.

"The vaccine effectiveness we saw in last year's flu season is encouraging. As both a research scientist and a primary care physician, I urge everyone to be vaccinated for flu this year and every year—it's good for each person's health and the health of your community."

Katherine Adams et al, Vaccine Effectiveness Against Pediatric Influenza-A–Associated Urgent Care, Emergency Department, and Hospital Encounters During the 2022–2023 Season: VISION Network, Clinical Infectious Diseases (2023). DOI: 10.1093/cid/ciad704

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'One and Done': Scientists Develop Vaccine That May Fight Any Viral Strain

'One and Done': Scientists Develop Vaccine That May Fight Any Viral Strain

By Dennis Thompson HealthDay Reporter

TUESDAY, April 16, 2024 (HealthDay News) -- Genetics-based “one-and-done” vaccines for the flu and COVID could prove more effective and easier to craft than current jabs, researchers report.

These new vaccines would target viruses using a different response to infection than what is prompted by current vaccines, researchers said.

Instead of teaching the immune system to create antibodies to fight off a specific virus, the new vaccine would instead teach the body to create small signaling RNA proteins that will shut down harmful viral spread.

This new approach could revolutionize current vaccine development, in which experts create vaccines based on predictions of which flu and COVID strains are likely to be most infectious, researchers argue.

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Instead, these RNA-promoting vaccines should be effective against all strains of a specific virus.

“What I want to emphasize about this vaccine strategy is that it is broad,” said researcher Rong Hai , a virologist with University of California, Riverside. “It is broadly applicable to any number of viruses, broadly effective against any variant of a virus and safe for a broad spectrum of people.”

“This could be the universal vaccine that we have been looking for,” Hai added in a university news release.

Traditionally, vaccines use dead or live but modified virus to prompt an immune response from the body. This immune response teaches the body how to recognize a germ and produce antibodies that specifically target and kill that bug.

The new vaccine also uses a live, modified version of a virus, but it doesn’t rely on the body having a traditional immune response that prompts the creation of antibodies, researchers said.

Instead, these vaccines teach the body to interfere with viral replication through the use of targeted RNA signaling proteins.

Everyone already has this natural response to infection, but viruses can produce their own proteins that block the body’s RNA response, explained researcher Showei Ding , a professor of microbiology at University of California, Riverside. The new vaccine teaches the body how to get around this viral defense.

There’s also little chance a virus could mutate to avoid this vaccine, Hia added.

“Viruses may mutate in regions not targeted by traditional vaccines. However, we are targeting their whole genome with thousands of small RNAs. They cannot escape this,” Hai said.

One such vaccine injection created for a mouse virus called Nodamura protected lab mice from lethal doses of the virus for at least 90 days, researchers report. Nine mouse days are roughly equivalent to one human year.

The new study was published April 15 in the Proceedings of the National Academy of Sciences .

University of California, Riverside, has been issued a U.S. patent on its new RNA vaccine technology, the researchers said.

The vaccine will be of particular help to newborns, who can’t receive current vaccines because their immune systems are underdeveloped, as well as people with diseases that compromise their immune systems, researchers said.

“That’s why our next step is to use this same concept to generate a flu vaccine, so infants can be protected,” Ding said. “If we are successful, they’ll no longer have to depend on their mothers’ antibodies.”

The new vaccine could also be delivered in the form of a spray, which will help people who are needle-shy.

“Respiratory infections move through the nose, so a spray might be an easier delivery system,” Hai said.

Ultimately, this strategy could be used to “cut and paste” vaccines for any number of viruses, the researchers noted.

“There are several well-known human pathogens; dengue, SARS, COVID. They all have similar viral functions,” Ding said. “This should be applicable to these viruses in an easy transfer of knowledge.”

More information

The U.S. Centers for Disease Control and Prevention has more on how traditional vaccines work .

SOURCE: University of California, Riverside, news release, April 15, 2024

Copyright © 2024 HealthDay . All rights reserved.

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A one-shot vaccine for COVID, flu and future viruses? Researchers say it's coming

New rna-based vaccine strategy could be a breakthrough: no boosters, no needles and far more rapid effects, by nicole karlis.

At the beginning of the pandemic, many people hoped that infections with SARS-CoV-2, the virus that causes COVID-19 — or vaccines against the virus — would provide  durable lifetime immunity, as is the case with diseases like  measles  or mumps. Instead, the COVID virus is more akin to the influenza virus, which mutates constantly and confers only short-term immunity . Both COVID and the flu require new and different vaccine formulas aimed at defeating newly circulating variants of the viruses. The inevitable result of this has been, for most of us, increasing vaccine fatigue.  

But what if it were possible to protect against COVID and the flu, and other unknown viruses that haven't yet emerged, with just one shot? If that became reality, seasonal or annual boosters would be part of the past. And what if such vaccinations didn't even require a needle?

While those possibilities may sound far in the future, scientists at the University of California, Riverside, believe they could become reality relatively soon — perhaps within the next five to 10 years. As illustrated in a paper just published in the Proceedings of the National Academy of Sciences , a new, RNA-based vaccine strategy could be effective against any viral strain to emerge in the future. This next generation of vaccines would theoretically offer protection against viruses we aren’t even aware of yet, and could be used safely on infants and people with compromised immune systems, who today must often opt out of vaccination to protect their health.

This new RNA-based technology, the research paper reports, would target a part of the viral genome that is common to all strains of any virus and would depend on a “second immune system” response. 

“We have a very strong reason to believe that all these other human viruses, like dengue virus and COVID-19, produce a protein that we can target to make a vaccine,” Shouwei Ding, distinguished professor of microbiology at UC Riverside and lead author of the paper, told Salon in a phone interview. With any future virus, "all we need to do is to identify the protein that can suppress RNAi.”

Here's what Ding was talking about. Traditional vaccines work by training the body to recognize and combat specific molecules found on a particular pathogen. For example, live-attenuated vaccines often use a weakened form of a virus to train the immune system. Once the weakened form of the virus is in the body, the immune system learns to recognize the antigen and develop immunity to it.

Another type of vaccine, based on "viral vectors," uses DNA and RNA to give cells a blueprint, rather than a piece of the pathogen itself, to build immunity. MRNA vaccines, like the best-known vaccines against COVID-19, use a synthetic version of single-stranded RNA to create a bespoke version of the mRNA within the body. This creates cells that can produce proteins like those found in a virus, and which then train the immune system to fight a disease before it enters a person’s bloodstream. 

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The new vaccine technology proposed in this paper would still use a live, modified version of a virus. But its effectiveness would not depend on the body's traditional immune response, which produces T-cells and memory B-cells. Instead, it would produce proteins that block a pathogen’s RNAi response, which is something all viruses create.

Researchers tested their theory in mice with a virus called Nodamura. The mice lacked T and B cells, but after one injection with the test vaccine, the mice were protected against the virus for at least 90 days. 

This new vaccine tech could be key to fighting bird flu, researchers say: "We are actively seeking funding to do just that.”

In 2013, this same group of researchers at UC Riverside published a paper showing that flu infections also cause people to produce RNAi molecules. Ding said their next step will be to generate a universal, one-time-use influenza vaccine that would be safe for very young infants. Current flu vaccines are only recommended for infants over the age of six months. Furthermore, this new vaccine would likely be delivered as a spray. As Salon has previously reported, vaccines that don’t require needles may one day become standard .

This intriguing report arrives at a moment when the bird flu virus, known as H5N1, has reportedly begun to spread among cattle. There has also been at least one confirmed human case. As Salon has reported , infectious disease experts do not expect bird flu to become a pandemic this year, that's a definite possibility in the future. One virologist told Salon she would recommend public vaccination against bird flu right now. No avian flu vaccines have yet been approved for use in humans, however, although several are  under development , none have been approved for use in humans yet.

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Ding said the vaccine his team is developing could be a contender: “That's what we're aiming for. We are actively seeking funding to do just that.”

Among the additional implications of this new vaccine technology, Ding said, could be more rapid protection than is now typical. “What we find is that two days after the shot, you are already fully protected,” he said. With current vaccines, "it will often take two weeks or more to be effective, and that's not very good for an emerging infection.” 

Ding said his team anticipates having a vaccine candidate ready for human clinical trials in about a year. After that, the traditional regulatory would likely take 5 to 10 years — although a new public health emergency, like the COVID pandemic, could speed that up considerably. 

about vaccines and viruses

• Do COVID-19 vaccines really have worse side effects than other vaccines? Here's what experts say
• US ranks last among peer nations for COVID-19 mortality: study
• Does your immune system need a workout? The bad science behind "immunity debt," explained

Nicole Karlis is a senior writer at Salon, specializing in health and science. Tweet her @nicolekarlis .

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Avian Influenza A(H5N1) U.S. Situation Update and CDC Activities

Current Situation Highlights Importance of Preventive Measures for People with Exposures

April 19, 2024 – CDC continues to respond to the public health challenge posed by the outbreak of avian influenza A(H5N1) virus, or “H5N1 bird flu” in dairy cows and other animals in the U.S. CDC is collaborating with partners including the U.S. Department of Agriculture (USDA), the Food and Drug Administration (FDA), and state public health and animal health officials to address this emerging infectious disease using a One Health approach . USDA is now reporting that eight U.S. states have outbreaks in dairy cattle and that the virus has spread through cattle movement between herds and also from dairy cattle premises into nearby poultry premises and has infected a number of barn cats. However, only one associated human case to date has been linked with this outbreak in dairy cows and was reported by Texas on April 1, 2024. [1] CDC’s response to this unprecedented outbreak of influenza A(H5N1) in dairy cattle and other animals most recently includes:

• Supporting states monitoring people with exposure to cows, birds, or other domestic or wild animals infected or potentially infected with influenza A(H5N1) viruses. Testing for these people is being done by state or local officials using a CDC test, and CDC is conducting confirmatory testing when needed.
• Continuing to work in the laboratory to better characterize the virus from the human case in Texas. This week CDC completed susceptibility testing for influenza antiviral medications that are used for seasonal influenza (e.g., the neuraminidase inhibitors oseltamivir, zanamivir and peramivir). Testing confirmed that the A(H5N1) virus was susceptible to all commercially available FDA-approved and recommended neuraminidase inhibitor antivirals. Testing to confirm susceptibility to baloxavir marboxil, a different antiviral medication, takes longer and is ongoing.
• Studying human sera (blood) from people vaccinated against A(H5) to confirm that existing A(H5N1) candidate vaccine viruses (CVVs) will provide protection against the A(H5N1) virus isolated from the human case in Texas. Manufacturers could use these CVVs to make a vaccine if needed. Preliminary genetic analysis  had suggested two existing CDC CVVs would offer protection against the virus isolated from the human case in Texas.
• Designing an epidemiological field study and preparing a multilingual and multidisciplinary team to travel on site to better understand the current outbreak, particularly the public health and One Health implications of the emergence of this virus in cattle.
• Engaging One Health partner organizations from public health, agriculture, milk regulatory officials, and others to share information and ensure preparedness to prevent and respond to this emerging infectious disease threat and for any potential human infections.
• Monitoring emergency department data and flu testing data in areas where A(H5N1) bird flu viruses have been detected in dairy cattle or other animals for any unusual trends in flu-like illness, flu, or conjunctivitis. So far, these data remain in expected ranges, and to date, surveillance systems do not show any unusual trends or activity.

This is a rapidly changing, emerging situation and CDC is committed to providing frequent and timely updates.

What Might Happen

The wide geographic spread of A(H5N1) bird flu viruses in wild birds, poultry, and some other mammals, including in cows, is creating additional opportunities for people to be exposed to these viruses. Therefore, there could be an increase in sporadic human infections resulting from bird, cattle, and other animal exposures, even if the risk of these viruses spreading to people has not increased. Sporadic human infections in the current context would not significantly change CDC’s risk assessment.

What Would Increase Public Health Risk

Identification of multiple simultaneous instances of A(H5N1) bird flu viruses spreading from birds, cattle, or other animals to people or certain genetic changes in circulating viruses could change CDC’s risk assessment because they could indicate the virus is adapting to spread more easily from animals to people. Additionally, if limited, non-sustained, person-to-person spread with this virus were to occur, that would also raise the public health threat because it could mean the virus is adapting to spread between people. Sustained person-to-person spread is needed for a pandemic to occur.

Because of the potential for influenza viruses to constantly change, continued surveillance and preparedness efforts are critical, and CDC is taking measures to be ready in case the current risk assessment for the general public changes. The immediate goal is to prevent further spread of this virus between animals and people. CDC will continue to monitor these viruses and update and adjust guidance as needed. As a reminder, while CDC believes the current risk of A(H5N1) infection to the general public remains low, people with close, prolonged, or unprotected exposures to infected birds, cattle, or other animals, or to environments contaminated by infected birds, cattle, or other animals, are at a greater risk of infection. CDC has interim recommendations for prevention, monitoring, and public health investigations of A(H5N1) viruses. CDC also has recommendations for worker protection and use of personal protective equipment (PPE) to reduce the risk of exposure . Compliance with these recommendations is central to containing the public health risk. Additionally, unpasteurized (“raw”) milk from sick cattle has tested positive for A(H5N1) viruses. Consumption of raw milk can be dangerous and is not recommended. The FDA has Questions and Answers Regarding Milk Safety During Highly Pathogenic Avian Influenza (HPAI) Outbreaks | FDA .

[1] The first human case of A(H5N1) bird flu in the United States was reported in 2022 in a person in Colorado who had direct exposure to poultry and was involved in the depopulating of poultry with presumptive A(H5N1) bird flu. The person recovered. Learn more at U.S. Case of Human Avian Influenza A(H5) Virus Reported | CDC Online Newsroom | CDC.

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Risk of bird flu spreading to humans is ‘enormous concern’, says WHO

Chief scientist voices fears about H5N1 variant that has ‘extraordinarily high’ mortality rate in humans

The World Health Organization has raised concerns about the spread of H5N1 bird flu, which has an “extraordinarily high” mortality rate in humans.

An outbreak that began in 2020 has led to the deaths or killing of tens of millions of poultry. Most recently, the spread of the virus within several mammal species, including in domestic cattle in the US, has increased the risk of spillover to humans, the WHO said.

“This remains I think an enormous concern,” the UN health agency’s chief scientist, Jeremy Farrar, told reporters in Geneva.

Cows and goats joined the list of species affected last month – a surprising development for experts because they were not thought susceptible to this type of influenza. US authorities reported this month that a person in Texas was recovering from bird flu after being exposed to dairy cattle, with 16 herds across six states infected apparently after exposure to wild birds.

The A(H5N1) variant has become “a global zoonotic animal pandemic”, Farrar said.

“The great concern of course is that in ... infecting ducks and chickens and then increasingly mammals, that virus now evolves and develops the ability to infect humans and then critically the ability to go from human to human,” he added.

So far, there is no evidence that H5N1 is spreading between humans. But in the hundreds of cases where humans have been infected through contact with animals over the past 20 years, “the mortality rate is extraordinarily high”, Farrar said, because humans have no natural immunity to the virus.

From 2003 to 2024, 889 cases and 463 deaths caused by H5N1 have been reported worldwide from 23 countries, according to the WHO, putting the case fatality rate at 52%.

The recent US case of human infection after contact with an infected mammal highlights the increased risk. When “you come into the mammalian population, then you’re getting closer to humans”, Farrar said, warning that “this virus is just looking for new, novel hosts”.

Farrar called for increased monitoring, saying it was “very important understanding how many human infections are happening ... because that’s where adaptation [of the virus] will happen”.

“It’s a tragic thing to say, but if I get infected with H5N1 and I die, that’s the end of it,” he said. “If I go around the community and I spread it to somebody else then you start the cycle.”

He said efforts were under way towards the development of vaccines and therapeutics for H5N1, and stressed the need to ensure that regional and national health authorities around the world had the capacity to diagnose the virus.

This was being done so that “if H5N1 did come across to humans, with human-to-human transmission”, the world would be “in a position to immediately respond”, Farrar said, calling for equitable access to vaccines, therapeutics and diagnostics.

• World Health Organization

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New bird flu infections: Here’s what you need to know

New cases in cows and a dairy worker in Texas highlight the need for vigilance and better strategies to protect animals and people.

• Cassandra Willyard archive page

This article first appeared in The Checkup, MIT Technology Review’s weekly biotech newsletter. To receive it in your inbox every Thursday, and read articles like this first, sign up here .  

A dairy worker in Texas tested positive for avian influenza this week. This new human case of bird flu—the second ever reported in the United States—isn’t cause for panic. The individual’s illness was mild—an eye infection—and they are already recovering. There’s still no evidence that the virus is spreading person to person. The person who became infected in Texas likely picked the virus up from infected cows or poultry on the farm where he works.

But the rash of recent infections among livestock is unsettling. Last month, goats in Minnesota tested positive. And avian influenza has now been confirmed in dairy cows in Texas, Michigan, Kansas, New Mexico, and Idaho. In some of those cases, the virus appears to have spread between cows. This week, let’s take a look at what we know about this new outbreak and what people are doing to prepare for further spread.  

The strain of flu infecting dairy cows—H5N1—is a highly pathogenic avian influenza. Scientists have been watching these viruses closely since the 1990s because of their potential to spark a pandemic. In 1997, avian influenza sickened humans for the first time. Eighteen people in Hong Kong became infected, and six died. 

Small spillovers into mammals aren’t uncommon for these viruses, especially in recent years. Avian influenza has been reported in mink, skunks, raccoons, coyotes, seals, sea lions, and bears, to name a few. But having the virus in domesticated mammals that come into frequent contact with humans is new territory. “Exactly what happens when an avian flu virus replicates in a cow and potentially transmits from cow to cow, we actually don’t have any idea at all,” says Richard Webby, a virologist at St. Jude Children’s Research Hospital who studies avian influenza.

Here’s the good news: even though the virus is infecting dairy cows (and now one dairy worker), “this is still very much a bird virus,” Webby says. Genetic sequencing by the USDA and the Centers for Disease Control suggests that these new infections are caused by a strain of flu that’s nearly identical to the virus circulating in wild birds. Few of the changes they did identify would allow it to spread more easily in mammals.

The spread of bird flu in cows is worrisome, but not as worrisome as it would be if the infections were happening in pigs, which are an ideal mixing vessel for flu virus. Pigs are susceptible to swine flu, avian influenza, and human influenza. That’s how swine flu emerged back in 2009— multiple viruses infecting pigs swapped genes , eventually giving rise to a virus capable of human transmission. 

Mammalian infections with bird flu have mostly been one-offs, Webby says. A mammal gets infected by eating a dead bird or ingesting bird droppings, but the infection doesn’t spread. One notable exception occurred in 2022, when H5N1 popped up on a mink farm in Spain and quickly jumped from barn to barn. Scientists also suspect that in rare cases, the virus has spread among family members . 

Cow-to-cow transmission hasn’t been confirmed, but the fact that some cows became infected after the arrival of cows from affected herds suggests that it may be occurring. That transmission may not be via coughs and sneezes—the traditional way flu gets passed on. It could be indirect. “So an infected cow drinks from a trough of water and the next cow comes along and drinks from that same trough,” Webby says.

How can we curb the spread among animals? That’s an ongoing debate. Vaccination is an option, at least for poultry. That’s common practice in China, Mexico, and a handful of other countries. Immunization doesn’t prevent infection, but it does reduce symptoms. That might curb the impact on flocks, but some experts are concerned that vaccinated flocks might allow the virus to spread undetected. Vaccination also would likely affect trade. Countries don’t want to import birds that might be infected. France decided to begin vaccinating ducks last year , and the USDA promptly announced it would restrict poultry imports from France and its trading partners. In the US, the current practice is to cull infected flocks . But there are signs that vaccination isn’t off the table. Last year the USDA began testing four vaccine candidates against the particular strain of H5N1 driving the current outbreak that has affected poultry across the globe. 

As a longer-term solution, researchers have also been working on creating genetically engineered animals that are resistant to bird flu. Last year, researchers created such chickens by using CRISPR to alter a single gene. 

For cattle, the current options to curb transmission are limited. Culling cattle would be a much harder sell because they’re so much more valuable than chickens. And cow vaccines for avian influenza don’t yet exist, although they would be relatively easy to produce. 

Bird flu has been on public health officials’ radar for more than two decades, and it has yet to make a jump into humans. “I do think that this particular virus has some fairly high hurdles to overcome to become a human-transmissible virus,” Webby says. But just because it hasn’t happened doesn’t mean it won’t: “We can be a little bit reassured that it’s not easy, but not assured that it can’t do it at all.”

Luckily, even if the virus suddenly acquired the ability to spread in humans, it would be vastly easier to develop a vaccine than it was to create one for covid-19. A vaccine already exists against H5N1. Doses of that shot are sitting in the country’s national stockpile. “This is one case we’re a little luckier because it’s a pathogen that we know. We know what this is and what we have in the freezer, so to speak. We have a little bit of a leg up on at least getting started,” Paul Marks, the FDA’s top vaccine regulator, told a reporter at the World Vaccine Congress this week . 

It’s not clear how well those doses would work against the current strain of H5N1. But many companies are already working on improved vaccines . Moderna plans to test an mRNA vaccine against the H5N1 strain causing the current outbreak. mRNA technology has a major advantage over traditional production methods for influenza vaccines, which grow the virus in eggs. In the event of a bird flu pandemic, eggs could be in short supply. Even if enough eggs were available, it could take half a year to develop a vaccine. mRNA technology, however, could shorten that timeline dramatically. 

That’s good news. With avian influenza surging across the globe, there are more opportunities than ever before for the virus to hit on a combination of genes that gives it the ability to easily infect humans. 

Now read the rest of The Checkup

Read more from mit technology review’s archive.

In a previous issue of The Checkup, Jessica Hamzelou explained what it would take for bird flu to jump to humans and why we don’t need to panic. Not yet, anyway. 

Google Earth can help scientists visualize the movement of H5N1 and perhaps even improve our ability to predict where outbreaks might occur. Rachel Ross had the story . 

Dig deep into the archives and you’ll find that Tech Review has been asking if bird flu will jump to humans for nearly two decades. Emily Singer report ed on efforts to answer this question in 2006.

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Original research

Effectiveness of influenza vaccination in the elderly: a population-based case-crossover study, chun-yu liang.

1 School of Nursing, National Defense Medical Center, Taipei, Taiwan

Shinn-Jang Hwang

2 Department of Family Medicine, Taipei Veterans General Hospital, Taipei, Taiwan

3 School of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan

Kuan-Chia Lin

4 Institute of Hospital and Health Care Administration, National Yang Ming Chiao Tung University, Taipei, Taiwan

Chung-Yi Li

5 Department of Public Health, College of Medicine, National Cheng-Kung University, Tainan, Taiwan

6 Department of Public Health, China Medical University, Taichung, Taiwan

Ching-Hui Loh

7 Center for Aging and Health, Hualien Tzu Chi Hospital, Hualien, Taiwan

8 School of Medicine, Tzu Chi University, Hualien, Taiwan

James Yi-Hsin Chan

9 Graduate Institute of Medical Sciences, National Defense Medical Center, Taipei, Taiwan

Kwua-Yun Wang

10 School of Nursing, National Defense Medical Centre, Taipei, Taiwan

11 Department of Nursing, Taipei Veterans General Hospital, Taipei, Taiwan

Associated Data

Data may be obtained from a third party and are not publicly available. The data in this study was provided by the Bureau of National Health Insurance. The data was used under license for the current study and not publicly available.

There is limited information regarding the effectiveness of influenza vaccines for older adults. Particularly, controlling for healthy senior bias is challenging in observational studies. We aimed to assess the efficacy of influenza vaccination in the elderly while addressing potential healthy senior bias and whether it was related to virus-vaccine strains matching.

To control between-individual confounder, we used a case-crossover study design using Taiwan’s National Health Insurance Research Dataset to analyse the association between influenza vaccination in older adults and the risk of hospitalisation for community-acquired pneumonia (CAP). Individuals were a ‘case’ in vaccinated years and a ‘control’ in unvaccinated years. The study periods were 2006/2007 and 2007/2008 seasons because virus-vaccine strains were matching in 2006/2007 season and unmatching in 2007/2008 season. Older adults were categorised into two groups: admitted for CAP during the pre-vaccination period (Admitted, n=311) and not hospital admitted for CAP (Non-admitted, n=572 432). The outcome was hospitalisation for CAP during the influenza period. Conditional logistic regression assessed influenza vaccine efficacy in reducing CAP.

Influenza vaccination had no protective effects in Admitted group. However, because of the tiny numbers in Admitted group, we could draw very limited conclusions. Receiving an influenza vaccine significantly prevented CAP in Non-admitted group only during the vaccine-circulating strain-matched year (OR, 0.72; 95% CI, 0.64 to 0.83). In addition, there was no protective effect against CAP hospitalisation among individuals with a Charlson Comorbidity Index score over 2.

Influenza vaccine efficacy was associated with vaccine-circulating strain-matched. When vaccine-circulating strains were all matching, receiving a shot reduced the probability of CAP hospitalisation by 28% in Non-admitted group. However, high comorbidity may reduce the vaccine efficacy. Therefore, it is necessary to educate older adults to receive annual influenza vaccination and in combination with non-pharmaceutical interventions to reduce the risk of CAP.

Strengths and limitations of this study

• We performed a case-crossover study design while addressing between-person confounders such as potential healthy senior bias, using a nationalised database.
• This study also controlled the within-person confounder, individual’s health status before receiving a shot, in estimating the effect of influenza vaccination.
• We used medical records to identify influenza vaccination status to avoid recall bias and misclassification.
• The population selected in this study were individuals who get vaccinated intermittently may be different from those who get vaccinated annually, which may affect the generalisation of the results.
• There was a tiny sample size in Admitted group, with very limited conclusions that we could draw.

The risks of hospitalisation, physician visits and emergency department visits for influenza and pneumonia in the elderly population aged 65 years and over are significantly increased during influenza seasons. 1 As recommended by the WHO, influenza vaccination is the major strategy to control influenza in high-risk populations. 2 The vaccines are licensed based on the results of randomised controlled trials that demonstrate safety and efficacy. The effectiveness of influenza vaccination in older individuals in the real world is a worldwide concern. 3

The benefits of influenza vaccination in the elderly are inconsistent and controversial. Several observational studies found that the influenza vaccine effectively reduced hospitalisation for pneumonia or influenza by 27%–33% and reduced the mortality rate by 48%–50% in community-dwelling elderly persons. 4 5 Another observational study noted that influenza vaccination was not associated with a reduced risk of community-acquired pneumonia (CAP). 6 Several studies revealed that the protective effects of the influenza vaccine depended on the match between the vaccine and circulating virus strains. 3 However, some studies indicated that mismatched influenza vaccines still provided protective effects. 4 7 8 The limited evidence on the effectiveness of influenza vaccination in older adults, and more research is needed. 3 9

Case–control methodology is frequently used to evaluate the protection afforded by vaccines in a real-world context. 10 Evidence from meta-analyses and review articles is mostly based on case–control and observational studies, which are likely influenced by the presence of bias due to difficulty in identifying and adjusting for confounders. 3 4 11–13 The limited evidence of observational studies was also attributed to healthy senior bias in influenza vaccination. 14–18 The individual’s vaccination history and immune status affect the protective response after influenza vaccination, which were not easy to adjust in a case–control study. 19 Some studies noted that morbidity and mortality were relatively low in vaccinees even before the start of the influenza season, which is related to bias. 20 21 Although cohort studies are generally adjusted for comorbidities, and case–control studies are matched for age and gender, these studies have not completely controlled for bias. 14 21 22 Therefore, we used a case-crossover study design for self-matching and determine the effectiveness of influenza vaccine. We aim to realise whether the protective effects of influenza vaccination depended on the virus-vaccine strains matching in the elderly while addressing potential healthy senior bias.

Influenza vaccine and circulating virus strains

To evaluate the effectiveness in preventing hospitalisation due to pneumonia by the level of viral circulation and vaccine matching in two consecutive years. We chose 2006/2007 season and 2007/2008 season as the study periods because virus-vaccine strains were all matching in 2006/2007 season and all unmatching in 2007/2008 season. The influenza vaccine strains were A/New Caledonia/20/99 (H1N1), A/Wisconsin/67/2005 (H3N2) and B/Malaysia/2506/2004 (type B) in 2006/2007 season. The epidemic influenza viral strains for 2006/2007 season were A/Wisconsin/67/2005-like (H3N2) and B/Malaysia/2506/2004-like (type B). The influenza vaccine strains in 2007/2008 season were A/Solomon Islands/3/2006 (H1N1), A/Wisconsin/67/2005 (H3N2) and B/Malaysia/2506/2004 (type B). 23 24 The epidemic influenza viral strains for 2007/2008 season were A/Brisbane/59/2007-like virus (H1N1), A/Brisbane/10/2007-like virus (H3N2) and B/Florida/4/2006-like virus (type B).

Source of data

This study used anonymised data of 30% of Taiwan’s total older population (>65 years) from 2005 to 2009. The study sample was randomly selected from all elderly insurers in Taiwan’s National Health Insurance Research Dataset (NHIRD). The decision to choose 30% of the total older population for analysis was made by the Review Committee of the National Health Research Insurance (NHRI) that manages the NHIRD with the reason of personal data protection. The NHI programme, which was instituted in March 1995, has contracts with almost every clinic and hospital in Taiwan. The NHI programme coverage rate has reached almost 99% in 1997 and has remained at that level ever since. 25

Definition of pre-vaccination, vaccination and influenza periods

As shown in figure 1 , the vaccination period was 1 October through 31 December, which coincided with the influenza vaccination programme governed by the Centers for Disease Control in Taiwan. We defined the influenza period as 1 January, after the close of the influenza vaccination period, through 30 April of the next year because influenza-like illness first peaked around early February, and the second peak occurred in March in Taiwan. 26 The pre-vaccination period was defined as the period from 1 May to 30 September, which was before the start of the influenza vaccination.

The case-crossover study design. CAP, community-acquired pneumonia.

Study cohort

A case-crossover study design was used to analyse associations between influenza vaccination in the elderly and their risk of hospitalisation for CAP in 2006–2007 and 2007–2008. Every individual was a ‘case’ during the influenza vaccinated years and a ‘control’ in unvaccinated years ( figure 1 ). As shown in figure 2 , the study cohort was established in the following steps. First, we included elderly people who were over 65 years as of 31 December 2006 and who were still alive on 1 May 2009. Second, we excluded the elderly who received pneumococcal vaccination from 2001 to 2008 to avoid data contamination from pneumococcal vaccination effects. Third, individuals hospitalised only once for CAP in the 2006 and 2007 pre-vaccination periods were excluded to ensure that these people had similar health conditions before receiving the influenza vaccine for reducing within-person confounder. Fourth, we categorised the elderly into the following groups: those who were never hospital admitted for CAP during the pre-vaccination period in two consecutive years (abbreviated Non-admitted) and those who were hospital admitted for CAP (abbreviated Admitted). Fifth, we identified individuals receiving only one influenza vaccination in calendar years 2006 and 2007 vaccination periods which meant that everyone could be a case in the vaccinated year and be a control in the unvaccinated year. Sixth, based on vaccination status, we divided these individuals into two groups. One group was the 2006 vaccinated and 2007 unvaccinated group (abbreviated 2006-vaccinated), and the other group was the 2006 unvaccinated and 2007 vaccinated (abbreviated 2007-vaccinated).

Sample flowchart of the study cohort. CAP, community-acquired pneumonia.

Definition of outcomes and other variables

The outcome was identified as hospitalisation for CAP during the influenza periods. An episode of CAP was defined as hospitalisation with a discharge diagnosis of pneumonia or influenza (ICD-9-CM codes 480.XX-487.XX). NHI claim records present each individual’s age, gender and comorbidity. Comorbidity was assigned a Charlson Comorbidity Index (CCI) 27 score based on admission and ambulatory care diagnosis codes (ICD-9-CM codes) between October 2005 and September 2006. A higher score indicates more severe comorbidity.

Patient and public involvement

It was a population-based study using the NHIRD for analysis. No patient was involved in the design, conduct, reporting or dissemination of this study.

Statistical analysis

A case-crossover study design was proposed to evaluate the effect of transient changes on the risk of acute-onset disease. As in a matched case–control study, inference is based on a comparison of exposure distribution rather than on the risk of disease. 28 In this study, each study individual had a 'control window', with the same risk of CAP hospitalisation before the vaccination period, and a 'case window', the period of different vaccination status in two consecutive years. Conditional logistic regression with each individual’s ID considered a stratum variable was applied to compare the risk of CAP hospitalisation during the influenza periods of vaccinated and unvaccinated years and to estimate the effectiveness of influenza vaccination. After adjustment for years, ORs and 95% CIs were derived from the regression coefficients and SEs of conditional logistic regression models. For all analyses, a 5% significance level was used. All statistical analyses were carried out using SAS (V.9.2).

As shown in figure 1 , 579 181 elderly did not receive pneumococcal vaccination from 2001 to 2008. The number of elderly in the Admitted group was 311, and the number of elderly in the Non-admitted group was 572 432. The Admitted group consisted of 47 cases who received influenza vaccination in 2006 but not in 2007 (2006-vaccinated) and 41 cases who received influenza vaccination in 2007 but not in 2006 (2007-vaccinated). In contrast, the Non-admitted group consisted of 70 488 cases who were vaccinated in 2006 but not in 2007 (2006-vaccinated) and 51 265 cases who were vaccinated in 2007 but not in 2006 (2007-vaccinated).

Among the Admitted and Non-admitted groups, the demographic characteristics of the 2006-vaccinated individuals were similar to the 2007-vaccinated individuals ( table 1 ). Nearly 66% of individuals in the Admitted group were aged ≥75 years old, the proportion of men was slightly higher than that of women and 21.6% had a CCI score ≥3. For individuals in the Non-admitted group, 35.6% were aged ≥75 years old, the number of men was approximately equal to women and only 3.8% had a CCI score ≥3. This result showed that the individuals in Non-admitted group were younger and healthier than the Admitted group.

Characteristics of the study cohorts according to admission status during the pre-vaccination period

*In each of the two consecutive years, the elderly who were hospital admitted with pneumonia during the pre-vaccination period.

†In two consecutive years, the elderly who were not hospital admitted with pneumonia during the pre-vaccination period.

‡CCI, Charlson Comorbidity Index.

The observed CAP hospitalisation rates of the Admitted group during the influenza periods for the 2006-vaccinated individuals in the vaccinated and unvaccinated years were 38.3% and 31.7%, respectively, and 26.8% and 27.7% in vaccinated and unvaccinated years, respectively, for the 2007-vaccinated individuals. The CAP hospitalisation rates of the Non-admitted group in vaccinated and unvaccinated years were 0.6% and 0.8%, respectively, for the 2006-vaccinated individuals and 0.8% and 0.7%, respectively, for the 2007-vaccinated individuals during the influenza period ( table 2 ).

Community-acquired pneumonia (CAP) hospitalisation rates of older adults during the influenza period

*In each of two consecutive years, the elderly who were hospital admitted with pneumonia during the pre-vaccination period.

‡Hospitalised for CAP during the influenza period.

Table 3 that shows the ORs for the risk of CAP hospitalisation for the Admitted group were non-significant in the 2006-vaccinated individuals (OR, 1.79; 95% CI, 0.60 to 5.26) and 2007-vaccinated individuals (OR, 0.67; 95% CI, 0.19 to 2.38). However, the sample size was tiny; we could not draw accurate conclusions. Influenza vaccination in the Non-admitted group was associated with a significantly reduced risk of CAP hospitalisation during the influenza period in the 2006-vaccination individuals (OR, 0.72; 95% CI, 0.64 to 0.83) but not in the 2007-vaccination individuals (OR, 1.06; 95% CI, 0.92 to 1.23). Influenza vaccination did not offer protection for the risk of CAP hospitalisation in the elderly who had a CCI score ≥3 during the influenza period in the 2006-vaccination individuals ( table 4 ).

ORs and 95% CIs for the risk of community-acquired pneumonia hospitalisation during the influenza period

Adjusted by year using conditional logistic regression.

†In two consecutive years, the elderly who were not hospital admitted with pneumonia during the pre-vaccination periods.

ORs for the risk of community-acquired pneumonia hospitalisation in Non-admitted individuals during the influenza period using stratified analysis

*In the two consecutive years, the elderly who were not hospital admitted with pneumonia during the pre-vaccination period.

†CCI, Charlson Comorbidity Index.

We provide evidence of the effects of the influenza vaccine in older adults in the real world using a population-based nationwide database. We estimated the effectiveness of the influenza vaccination in protecting people aged 65 years or older from CAP hospitalisation using a case-crossover study design. The case-crossover study design allows the case to serve as his/her own control to completely control for between-person confounders, such as the healthy senior bias that is generally mentioned in case–control studies. It is used to investigate transient effects of accurately recorded preventive agents, and it is better than cohort designs for vaccines. 28 29 The case-crossover comparisons of vaccine effectiveness reduce confounders that are stable over time in a person, including health behaviours and the tendency to seek professional care. 29 For a case-crossover study, there should be a ‘washout’ period to avoid carry-over effects. 30 In our study, the 2006-vaccinated group had a 12-month washout period from the end of the first vaccination period to the second outcome period. The prior vaccination in the previous year does not influence the seroprotection rates 12 months post-influenza vaccination, 19 which means there were no carry-over effects in the 2006-vaccined group. Because the case-crossover design compares the same person at different times, any time variation should be a concern. 31 Therefore, we stratified the individuals into a 2006-vaccinated group and a 2007-vaccinated group for analysis because the vaccine strains, circulating viruses and magnitude of influenza epidemics changed year by year. We provide evidence that the case-crossover study design is suitable for evaluations of vaccine effects, and it may be used in future research. In addition, we used medical records to identify influenza vaccination status, which is more reliable than recall, to avoid the misclassification that may bias the effectiveness estimate towards or away from the null hypothesis. 32 We used several ways in study design to increase the reliability of the influenza vaccine effects.

An individual’s health status before an influenza shot is a main within-person confounder in evaluations of vaccine effects. 6 9 We controlled for the confounder, the individual’s health status before receiving the vaccine, by dividing individuals into Admitted and Non-admitted groups. We showed that these two groups had different responses to the effects of the influenza vaccine. Compared with Non-admitted group, the individuals in Admitted group were older and had higher CCI scores that might be the reason for the different protection effects. However, our sample numbers in the Admitted group were insufficient to show good power and make a firm conclusion. Further study with a larger sample size is needed. For the Non-admitted group, influenza vaccination had a protective effect in 2006/2007 season but not in 2007/2008 season. This finding may be attributed to difference in the virus-vaccine match, which was excellent for 2006/2007 season but poor for 2007/2008 season. 23 This result is similar to the results of previous meta-analyses that indicates vaccine protection against CAP admission varies according to vaccine-circulating strain-matched or not. 3 5 In addition, because of the possible immune memory and heterotypic cross-protection by influenza vaccination. 33 Annual influenza vaccination is still a cost-effective strategy to prevent CAP.

We assessed factors that affected the effectiveness of influenza vaccination in the prevention of CAP admissions during influenza periods in the Non-admitted group in vaccine-circulating strain-matched years. Previous studies mentioned that comorbidity, frailty and age were confounding factors for the assessment of influenza vaccine effects. 3 34 Our study showed that vaccine effectiveness against CAP was affected by comorbidity but not by age. The progressive decline in systemic immunity may be one reason for comorbidities in the elderly and their possible influence on the reduction in vaccine response. 35 Vaccination had a smaller effect on reducing the risk of CAP hospitalisation in older individuals who had a higher comorbidity in the present study, even in vaccine-circulating strain-matched seasons.

Influenza viruses primarily spread via contact, droplets and airborne transmission when people with the influenza cough, sneeze or talk, which is similar to COVID-19. 36 37 The policy of yearly influenza vaccination is highly recommended in protecting against influenza viruses. 38 Because some older adults do not feel necessary for influenza vaccination, multiple prompts from family, particularly from healthcare providers, were important triggers for receiving immunisation. 39 However, we demonstrated that vaccination only had protective effects when vaccine-circulating strain-matched. The reduced vaccine effects even in the vaccine-circulating strain-match seasons may be attributed to complex health problems in older adults. To protect against influenza, non-pharmaceutical interventions, including hand washing, social-distancing, covering your mouth and nose with a mask when around others, and increasing ventilation may be recommend, especially for older adults with high comorbidity. 38 40 Healthy habits and lifestyle, including plenty of sleep, physical activity, stress management, drinking plenty of fluids and eating nutritious food, are also helpful to prevent influenza. 41

The following limitations were identified in this study. First, the population selected in this study were individuals with intermittent vaccination (ie, one vaccine in two consecutive years). The percentage of intermittent vaccination sample was 28% among Admitted Group, and 21% among Non-admitted group of the population. It is unclear how that crossover subgroup differs from the overall cohort, and whether the relationship observed for that subgroup would generalise to the overall cohort and the larger community of older adults. Second, the specific outcome for the evaluation of the effects of influenza vaccine needs to be confirmed by clinical laboratory data. Because there was no laboratory data in NHIRD, we used CAP as a common, but less specific, outcome in this study. Third, tiny numbers in Admitted group affected the results’ accuracy and only limited conclusions that we could draw.

Conclusions

The present study provides evidence that the effects of influenza vaccination against CAP in older adults depends on the vaccine-circulating strain-matched. The policy of providing a free influenza vaccine to older adults is highly supported. An individual’s comorbidity may reduce the influenza vaccine effects. Therefore, healthcare providers should use vaccination in combination with non-pharmaceutical interventions to keep older adults away from influenza.

Supplementary Material

Contributors: C-Y L and K-Y W designed the model and the computational framework. C-YL analysed the data with support from C-Y L and K-C L. C-Y L wrote the manuscript with support from S-J H and K-Y W. K-Y W made critical revisions to the paper for important intellectual content. JY-H C and C-H L contributed to the interpretation of the results. K-Y W responsible for the overall content as the guarantor. All authors discussed the results and commented on the manuscript.

Funding: This work was supported by the Taipei Veterans General Hospital (grant numbers V100C-211).

Competing interests: None declared.

Patient and public involvement: Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

Provenance and peer review: Not commissioned; externally peer reviewed.

Data availability statement

Ethics statements, patient consent for publication.

Not applicable.

Ethics approval

The Review Committee of NHRI and Institutional Review Board of the Taipei Veterans General Hospital approved the study protocol (No. 2011-03-006IC).

What You Should Know About the RSV Vaccines

The virus can be serious in older adults and infants.

This article is based on reporting that features expert sources.

RSV Vaccines: Who Should Have One?

Key Takeaways:

• RSV is a common respiratory virus that causes mild symptoms but can cause severe illness, especially in older adults, infants and individuals with weakened immune systems.
• Currently, the two RSV vaccines available for adults ages 60 and older are Pfizer's Abrysvo and GSK's Arexvy.
• Pregnant women between weeks 32 and 36 and infants younger than 8 months can receive Abrysvo and a preventive monoclonal antibody immunization, called nirsevimab (Beyfortus), respectively.
• For older adults, the optimal time to get the RSV vaccine is in August or September.
• The RSV vaccines are typically covered by private health insurance, Medicare Part D and Medicaid.

When it comes to seasonal viruses, you’re probably concerned about the flu and COVID. On the other hand, the respiratory syncytial virus, or RSV for short, may not be on your radar. But it should be.

Here's what you need to know about RSV and the vaccines.

What Is RSV?

RSV is a common respiratory virus that typically causes mild, cold-like symptoms, such as a runny nose, coughing, sneezing and sometimes a fever. However, it can be dangerous in some people, particularly babies, older adults and those with chronic medical conditions, such as heart or lung disease.

In fact, it’s estimated that each year 60,000 to 160,000 older adults in the U.S. are hospitalized and 6,000 to 10,000 die as a result of RSV infection, according to the Centers for Disease Control and Prevention.

Getty Images

“For a long time, it was thought to be a pediatric virus – it’s the leading cause of hospitalizations among infants in the U.S.,” says Dr. William Schaffner, a professor of infectious diseases at the Vanderbilt University Medical Center in Nashville. “Over the last 20 years, it’s become apparent with improved diagnostic studies that RSV can cause as much serious respiratory illness in older adults as flu. Older adults are at increased risk for complications, such as hospitalization, pneumonia and ending up in the (intensive care unit).”

As with the flu and COVID, you can get repeated infections of RSV throughout your life.

“For older adults with other medical problems, this can be a very dangerous virus. Unlike with influenza, we don’t have antiviral drugs to treat it,” says Dr. Gregory Poland, a professor of medicine and infectious diseases and director of the Mayo Vaccine Research Group at the Mayo Clinic in Rochester, Minnesota. “It’s something to take seriously.”

Fortunately, RSV vaccines are now available for those who are at highest risk of getting severely sick.

What RSV Vaccines Are Available?

To protect those who are at high risk for severe illness or complications from RSV, various immunizations are now available.

Here’s a look at the guidelines for each population:

Older adults

Two RSV vaccines – Pfizer Abrysvo and GSK Arexvy – were approved in 2023 by the Food and Drug Administration for adults ages 60 and older. However, this doesn’t mean all adults in this age group should get it as a matter of routine: It falls under the heading of “shared clinical decision-making,” meaning it’s an issue doctors and patients should discuss together based on a patient’s individual health status, Poland explains.

Your doctor is likely to recommend it if you have any of the following health conditions:

• Lung disease.
• Heart disease.
• Kidney or liver disorder.
• A weakened immune system from an illness, like leukemia, or you're taking immune-suppressing medications.

In a 2023 study published in The New England Journal of Medicine, researchers gave nearly 25,000 adults ages 60 and older either the RSV vaccine or a placebo. Over the course of seven months, they found that the vaccine was 83% effective at preventing RSV infection and 94% effective against severe RSV infection among older adults. Schaffner says the two vaccines are equally effective.

Pregnant women

Pregnant women between weeks 32 and 36 during September through January can get the maternal Pfizer Abrysvo vaccine to protect their babies. After vaccination, the mother-to-be can pass on antibodies to the baby for protection after birth.

Infants (younger than 8 months)

The CDC recommends an RSV preventive monoclonal antibody immunization, called nirsevimab (Beyfortus), for all infants younger than 8 months who are born during or are entering their first RSV season – if the mother didn’t get the RSV vaccine during the pregnancy or if the baby was born within 14 days of her getting the maternal vaccine. This vaccine is given as a shot into the baby’s thigh muscle.

When Is the Best Time to Get the Vaccine?

For older adults, the optimal time to get the RSV vaccine is in the late summer or early fall, typically August or September – just before the virus usually starts to circulate in the community. For the sake of convenience, people can get the RSV vaccine at the same time as the flu vaccine or the COVID vaccine .

The RSV season generally goes through March, though the season changes every year.

“Some years, it’s longer or shorter,” says Dr. Lana Dbeibo, an infectious diseases physician at Indiana University.

Right now, it isn’t clear how often the vaccine should be given to people at high risk for severe RSV illness, but “it looks like it will protect for longer than one year,” Schaffner says. More research is underway to determine the optimal frequency.

Common RSV Vaccine Side Effects

The most common side effects of the RSV vaccine include:

• Pain, redness and swelling at the injection site.
• Muscle or joint pain.

Side effects are typically mild and usually resolve in a day or two. During the clinical trial for the vaccine, a small number of participants experienced neuroinflammatory reactions, such as Guillain-Barré syndrome (a rare disorder that can lead to muscle weakness and sometimes temporary paralysis), or atrial fibrillation (irregular heart rhythm). Researchers are conducting additional studies to investigate whether the vaccines caused these reactions or if they occurred coincidentally.

Are the RSV Vaccines Covered by Insurance?

Yes, the RSV vaccine is usually covered by health insurance, including private plans, Medicare and Medicaid:

• Private health insurance . The RSV vaccine is covered by private health insurance plans for adults ages 60 and older. Private health plans are required to cover new vaccine recommendations, including the RSV vaccine, but it's best to check with your insurance provider first.
• Medicare Part D. The RSV vaccine is covered by Medicare Part D for older adults at no cost.
• Medicaid. Effective October 1, 2023, Medicaid covers the maternal and infant RSV vaccine for pregnant people and infants under 8 months at no cost.

Other Ways to Protect Yourself

You can take the same precautions to protect yourself from RSV as you do for COVID and the flu.

“When viruses are active in the community, wear a mask when you go indoors (in public settings) and think carefully about when and where you go out,” Schaffner advises. “You may want to stream a movie instead of going to one.”

It’s also smart to stay away from people who are coughing or sneezing and to stay home when you’re sick.

"RSV transmits by touch, so make sure you’re washing your hands regularly,” Dbeibo says. “Clean frequently touched surfaces, like phones and TV remotes, regularly (with a disinfectant)."

What Is the Tomato Flu Virus?

Shanley Chien Dec. 26, 2022

The U.S. News Health team delivers accurate information about health, nutrition and fitness, as well as in-depth medical condition guides. All of our stories rely on multiple, independent sources and experts in the field, such as medical doctors and licensed nutritionists. To learn more about how we keep our content accurate and trustworthy, read our  editorial guidelines .

Dbeibo is an infectious diseases physician and associate vice chair for quality and safety for the department of medicine at Indiana University.

Poland is a professor of medicine and infectious diseases and director of the Mayo Vaccine Research Group at the Mayo Clinic in Rochester, Minnesota.

Schaffner is a professor of infectious diseases at the Vanderbilt University Medical Center in Nashville.

Tags: vaccines , health , senior health , children's health , women's health , health care , health insurance , public health , Medicare , Medicaid , respiratory problems

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