Influenza, HumanNCT05110911
Does Repeat Influenza Vaccination Constrain Influenza Immune Responses and Protection
An observational study of Influenza, Human and SARS-CoV-2 Infection, run by University of Melbourne at 6 sites in Australia.
Trial summary
The objectives of this study are to understand the long-term consequences of repeated annual influenza vaccination among healthcare workers (HCWs) and to use statistical and mathematical modelling to elucidate the immunological processes that underlie vaccination responses and their implications for vaccination… Read more about this study
- Who is it for?
- Ages 18 to 60 yearsHealthy volunteers can take part
- Conditions the study is for
- Influenza, Human, SARS-CoV-2 Infection
- What is being tested?
- Influenza vaccination: Fluarix Tetra, Vaxigrip Tetra, Fluquadri, Fluad Quad, Afluia Quad, Flucelvax Quad and SARS-CoV-2 vaccination: Comirnaty or Vaxzevria
- Type of treatment
- Vaccines
- How many people
- 1,500 participants
- Where
- 6 sitesAustralia
- Study dates
- 2 Apr 2020to 30 Jun 2025
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 60 years
- All sexes
- Healthy volunteers accepted
- Adult
Study population: Healthcare workers (including staff, honorary staff, students and volunteers) from six participating hospitals (or healthcare services) who are eligible for the hospitals' free vaccination programmes, at the time of recruitment.
Who may be able to join
- Eligible participants will be recruited from 1 of 6 participating hospitals and will meet the following criteria:
- Personnel (including staff, honorary staff, students and volunteers) located at a participating hospital or healthcare service at the time of recruitment who would be eligible for the hospital's free vaccination programme
- Be aged ≥18 years old and ≤60 years old;
- Have a mobile phone that can receive and send SMS messages;
- Willing and able to provide blood samples;
- Available for follow-up over the next 7 months;
- Able and willing to complete the informed consent process.
- There are no restrictions on the type of healthcare worker (HCW) that can be recruited into the study in terms of their job role. HCWs can be any hospital staff, including clinical, research, administrative and support staff.
Who cannot join
- Immunosuppressive treatment (including systemic corticosteroids) within the past 6 months;
- Personnel for whom vaccination is contraindicated at the time of recruitment.
Trial locations and contacts
6 sites in 1 country.
6 sites in 1 country
Australia6 sites
Women's and Children's Hospital
Adelaide, South Australia, 5006
Queensland Children's Hospital
Brisbane, Queensland, 4101
The Alfred
Melbourne, Victoria, 3004
Perth Children's Hospital
Nedlands, Western Australia, 6009
John Hunter Hospital
New Lambton Heights, New South Wales, 2305
The Children's Hospital at Westmead
Westmead, New South Wales, 2145
About this study
The objectives of this study are to understand the long-term consequences of repeated annual influenza vaccination among healthcare workers (HCWs) and to use statistical and mathematical modelling to elucidate the immunological processes that underlie vaccination responses and their implications for vaccination effectiveness. These objectives will be achieved by pursuing three specific aims:
- To study the immunogenicity and effectiveness of influenza vaccination by prior vaccination experience
- To characterize immunological profiles associated with vaccination and infection
- To evaluate the impact of immunity on vaccination effectiveness.
Read more
Under Aim 1, a cohort of hospital workers will be recruited and followed for up to 4 years to assess their pre- and post-vaccination and post-season antibody responses, and their risk of influenza infection. These outcomes will be compared by vaccination experience, classified as frequently vaccinated (received ≥3 vaccines in the past 5 years), infrequently vaccinated (<3 vaccinations in past 5 years), vaccinated once, vaccine naïve and unvaccinated.
In Aim 2, intensive cellular and serological assessments will be conducted to dissect the influenza HA-reactive B cell and antibody response, and build antibody landscapes that typify the different vaccination groups.
In Aim 3, the data generated in Aims 1 and 2 will be used to develop a mathematical model that considers prior infection, vaccination history, antibody kinetics, and antigenic distance to understand the effects of repeated vaccination on vaccine effectiveness.
Completion of the proposed research will provide evidence to inform decisions about continued support for influenza vaccination programs among HCWs and general policies for annual influenza vaccination, as well as much needed clarity about the effects of repeated vaccination.
In March-April 2020 pursuant to the SARS-CoV-2 global pandemic an administrative supplement added a SARS-CoV-2 protocol addendum for follow-up of COVID-19 infections amongst our HCW participant cohort.
The following objectives were added:
- To estimate risk factors and correlates of protection for SARS-CoV-2 infection amongst HCW
- To characterize viral kinetics and within-host viral dynamics of SARS-CoV-2 infecting HCW
- To characterize immunological profiles following infection by SARS-CoV-2
- To characterize immunological profiles following vaccination for SARS-CoV-2.
Read the detailed description
Over 140 million Americans are among the more than 500 million people who receive influenza vaccines annually. An important subgroup are healthcare workers (HCWs) for whom vaccination is recommended, and sometimes mandated, to protect themselves and vulnerable patients from influenza infection. However, there have been no large, long term studies of HCWs to support the effectiveness of these policies. HCWs are now a highly vaccinated population, the effects of which are also poorly understood. Mounting evidence suggests antibody responses to vaccination can be attenuated with repeated vaccination, which is corroborated by reports of poor vaccine effectiveness among the repeatedly vaccinated. Thus, there is a compelling need to directly evaluate HCW vaccination programs. The long term goal is to improve the efficient and effective use of influenza vaccines.
The specific objectives of this study are to understand the long-term consequences of repeated annual influenza vaccination among HCWs and to use statistical and mathematical modeling to elucidate the immunological processes that underlie vaccination responses and their implications for vaccination effectiveness. These objectives will be achieved by pursuing three specific aims:
- To study the immunogenicity and effectiveness of influenza vaccination by prior vaccination experience
- To characterize immunological profiles associated with vaccination and infection
- To evaluate the impact of immunity on vaccination effectiveness.
Under Aim 1, a cohort of hospital workers will be recruited and followed for up to 4 years to assess their pre- and post-vaccination and post-season antibody responses, and their risk of influenza infection. These outcomes will be compared by vaccination experience, classified as frequently vaccinated (received ≥3 vaccines in the past 5 years), infrequently vaccinated (<3 vaccinations in past 5 years), vaccinated once, vaccine naïve and unvaccinated.
In Aim 2, intensive cellular and serological assessments will be conducted to dissect the influenza HA-reactive B cell and antibody response, and build antibody landscapes that typify the different vaccination groups.
In Aim 3, the data generated in Aims 1 and 2 will be used to develop a mathematical model that considers prior infection, vaccination history, antibody kinetics, and antigenic distance to understand the effects of repeated vaccination on vaccine effectiveness. This approach is innovative because it will provide insights into the effect of complex immunological dynamics on infection outcomes, thereby representing a novel departure from previous studies, which have ignored these difficult-to-measure processes. Completion of the proposed research will provide evidence to inform decisions about continued support for influenza vaccination programs among HCWs and general policies for annual influenza vaccination, as well as much needed clarity about the effects of repeated vaccination.
In March-April 2020 pursuant to the SARS-CoV-2 global pandemic an administrative supplement added a SARS-CoV-2 protocol addendum for follow-up of COVID-19 infections amongst our HCW participant cohort.
The following objectives were added under the supplement IRB application:
- To estimate risk factors and correlates of protection for SARS-CoV-2 infection amongst HCW
- To characterize viral kinetics and within-host viral dynamics of SARS-CoV-2 infecting HCW
- To characterize immunological profiles following infection by SARS-CoV-2
- To characterize immunological profiles following vaccination for SARS-CoV-2.
- Conditions
- Influenza, Human, SARS-CoV-2 Infection
- Being tested
- Influenza vaccination: Fluarix Tetra, Vaxigrip Tetra, Fluquadri, Fluad Quad, Afluia Quad, Flucelvax Quad, SARS-CoV-2 vaccination: Comirnaty or Vaxzevria
- Keywords
- Vaccine Response Impaired, Influenza, Human, Health Personnel, Influenza Vaccines, SARS-CoV-2 Infection, Immunologic Memory, Vaccination
- Medical subject headings
- Influenza, Human, COVID-19
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Influenza vaccination: Fluarix Tetra, Vaxigrip Tetra, Fluquadri, Fluad Quad, Afluia Quad, Flucelvax QuadBiological
Influenza vaccine made available to healthcare workers at the participating healthcare sites, as part of their free vaccination campaigns for healthcare workers.
SARS-CoV-2 vaccination: Comirnaty or VaxzevriaBiological
SARS-CoV-2 vaccine made available to healthcare workers at the participating healthcare sites, as part of their free vaccination campaigns for healthcare workers.
| Study group | Role | What they receive |
|---|---|---|
| Healthcare Workers | Eligible participants will be recruited from 1 of 6 participating hospitals in Australia and will meet the following criteria: personnel (including staff, honorary staff, students and volunteers) located at a participating hospital or healthcare service at the time of recruitment who would be eligible for the hospital's free vaccination programme; be aged ≥18 years old and ≤60 years old; have a mobile phone that can receive and send SMS messages; willing and able to provide blood samples; available for follow-up over the next 7 months; able and willing to complete the informed consent process.
There are no restrictions on the type of healthcare worker (HCW) that can be recruited into the study in terms of their job role. HCW will be any hospital staff, including clinical, research, administrative and support staff. Receives: Biological: Influenza vaccination: Fluarix Tetra, Vaxigrip Tetra, Fluquadri, Fluad Quad, Afluia Quad, Flucelvax Quad; Biological: SARS-CoV-2 vaccination: Comirnaty or Vaxzevria |
What is being measured
The primary outcome is the main question the study is designed to answer.
Seropositivity post-vaccination (influenza vaccine)
Seropositivity among vaccination groups will be calculated and compared using logistic regression, with seropositivity coded as 1 if the titre ≥40, and 0 if the titre is <40. We will test for trend among vaccination groups, assuming seropositivity will be lowest in the most highly vaccinated.
Measured: Post-vaccination blood draws are at 14-21 days post vaccination. Collected each year 2020-2023 post annual influenza vaccination.
Seropositivity post-season (influenza vaccine)
Seropositivity among vaccination groups will be calculated and compared using logistic regression, with seropositivity coded as 1 if the titre ≥40, and 0 if the titre is <40. We will test for trend among vaccination groups, assuming seropositivity will be lowest in the most highly vaccinated.
Measured: End of the season blood draws are in October or November each year, at the conclusion of Australia's annual influenza season. Vaccination usually occurs in April or May. Collected each year 2020-2023 post annual influenza season.
Fold-rise in geometric mean antibody titre (GMT) pre- to post-vaccination
The changes in GMT from pre- to post-vaccination. Seroconversion is defined as samples with 4-fold increases in hemagglutination inhibition (HI) titre.
Measured: Changes from day 0 to day 14-21 post influenza vaccination. Collected each year 2020-2023 pre and post annual influenza vaccination.
Fold-change in geometric mean antibody titre (GMT) post-vaccination to post-season
The changes in GMT from post-vaccination to post-season.
Measured: Changes from day 14-21 to post-season. Influenza season in Australia is approximately May to November. Pre-vaccination to post-season is approximately April or May to October or November each year. Collected each year 2020-2023.
Seroconversion fraction post-vaccination
The proportion of samples with 4-fold increases in hemagglutination inhibition (HI) titre. Seroconversion post-vaccination will be calculated and compared among vaccination groups by logistic regression, with seroconversion coded as 1 if the fold-rise in titre is ≥4 and 0 if the fold-rise in titre is <4. We will test for trend, assuming seroconversion will be lowest in the most highly vaccinated.
Measured: Changes from day 0 to day 14-21 post influenza vaccination. Collected each year 2020-2023 pre and post annual influenza vaccination.
Secondary outcomes (24)
Healthcare workers (HCWs) PCR-positive for influenza at the end of each season
Proportion of HCWs that are PCR-positive for influenza at the end of each season.
Measured: Influenza season in Australia is approximately May to November. Follow up for PCR-positives from approximately April/May to October/November each year from 2020-2023.
Influenza attack rate at the end of each season
Evidence of influenza infection will be based on RT-PCR-confirmed infection, only, as serological evidence may be biased in vaccinees who elicit a good antibody response to vaccination. Attack rates will be calculated for each vaccination group as the number of cases during the person-time at risk.
Measured: Person-time at risk, during influenza season. Influenza season in Australia is approximately May to November. Follow up for PCR-positives from approximately April/May to October/November each year from 2020-2023.
Vaccine efficacy (VE)
VE will be estimated using a Cox proportional hazards regression model comparing the risk of influenza infection (coded as 1 for infected or 0 for uninfected) among healthcare workers (HCWs) by vaccination status: VE = (1-HRadj) × 100%. If there are sufficient cases, the model will be adjusted for potential confounders (e.g. age group), and factors that may modify the risk of infection. Using virus characterization data, we will assess if failures are associated with antigenic mismatch.
Measured: Person-time at risk, during influenza season. Influenza season in Australia is approximately May to November. Follow up for PCR-positives from approximately April/May to October/November each year from 2020-2023.
Duration of illness (influenza)
The number of days ill with influenza (count) will be compared among vaccination groups, adjusted for age. Because of the excess of 0 counts (people who never get infected), zero-inflated negative binomial regression will be used.
Measured: Days ill, during influenza season. Influenza season in Australia is approximately May to November. Follow up for PCR-positives from approximately April/May to October/November each year from 2020-2023.
Haemagglutinin (HA) antibody landscapes for vaccine-naïve and highly-vaccinated healthcare workers (HCWs)
By collating the results of many antibody assays to historical influenza strains, it is possible to visualize the landscape of an individual's responses to vaccination and infection. We are using strains going back to 1968 when A(H3N2) emerged in humans.
Measured: Bloods on day 0, day 7, day 14-21 post influenza vaccination and end of season. Collected each year 2020-2023 pre and post annual influenza vaccination and end of influenza season.
Haemagglutinin (HA) antibody landscapes for infected versus uninfected healthcare workers (HCWs)
By collating the results of many antibody assays to historical influenza strains, it is possible to visualize the landscape of an individual's responses to vaccination and infection. We are using strains going back to 1968 when A(H3N2) emerged in humans.
Measured: Bloods on day 7 and day 14-21 post influenza infection. Collected each year 2020-2023 along with pre and post annual influenza vaccination and end of influenza season bloods.
Enumeration of cells
Enumeration of influenza haemagglutinin (HA)-reactive B cells, and of subsets with phenotypic markers indicative of activation, and of memory versus naïve status, for vaccine-naïve, highly vaccinated and infected healthcare workers (HCWs) (i.e. we are comparing frequency fold-change/ratio between groups highly vaccinated and infrequently vaccinated).
Measured: Bloods on day 0 and day 14-21 post influenza vaccination and post infection. The key indicator is the frequency of these B cells on day 14 post-vaccination relative to pre-vaccination frequencies. Collected each year 2020-2023.
B cells
B cell receptor gene usage by influenza haemagglutinin (HA)-reactive B cells recovered post vaccination and post infection from selected vaccine naïve, highly vaccinated and infected healthcare workers (HCWs) with distinct antibody response profiles. In depth characterization of HA antigenic sites recognized by serum antibodies from selected HCW including vaccine non-responders who lack seroprotection, and vaccine serological responders who fail to be protected. This analysis will largely be performed on B cells detected on day 7 post vaccination, when there is the greatest potential to differentiate between vaccine reactive B cells that have come from naïve versus memory pools.
Measured: Blood draws on day 7 post influenza vaccination and post infection. Collected each year 2020-2023.
Quantify biological mechanisms that shape the antibody response
Models of antibody dynamics and individual-level exposures will be develop to quantify the different aspects of the antibody response that generated observed immunological profiles.
Measured: Bloods on day 0, day 7, day 14-21 post influenza vaccination, day 7, day 14-21 post infection and end of season. Collected each year 2020-2023.
Estimate protective titres
As the model is refined we will identify a minimum set of titres against past or forward strains that capture the underlying 'smooth' antibody landscape and provide a reliable correlate of protection.
Measured: Bloods on day 0, day 7, day 14-21 post influenza vaccination, day 7, day 14-21 post infection and end of season. Collected each year 2020-2023.
Optimal influenza vaccination strategy for healthcare workers (HCWs) under different vaccine availability
With our model in place, we will compare the performance of current vaccination programs with simulated alternatives to predict the impact of repeated vaccination and circulating virus on vaccine efficacy (VE) under different scenarios. In particular, we will examine the potential impact of: highly-valent vaccines, which include more than a single strain for each subtype; universal vaccines that generate a broadly cross-reactive response against conserved influenza epitopes; and near-universal vaccines that produce a broader response, but still have potential to generate effects such as antibody focusing or seniority, which could reduce effectiveness.
Measured: Bloods on day 0, day 7, day 14-21 post influenza vaccination, day 7, day 14-21 post infection and end of season. Collected each year 2020-2023.
Estimated SARS-CoV-2 attack rates among symptomatic and asymptomatic healthcare workers (HCWs)
Symptomatic attack (incidence) rates will be calculated as the number of cases testing positive by RT-PCR during the person-time at risk. The asymptomatic incidence proportion will be calculated as the number of HCWs with evidence of sero-conversion and no acute respiratory infection reported among all HCWs followed during the same period.
Measured: Follow-up period 2020-2023.
Case-hospitalization risk
The hospitalization risk (or incidence proportion) will be calculated as the number of healthcare workers (HCWs) hospitalized due to COVID-19 among all HCW with either asymptomatic or symptomatic evidence of infection during the same period.
Measured: Follow-up period 2020-2023.
Risk factors for asymptomatic, mild and severe SARS-CoV-2 infection
The predictors of severe infection will be estimated using a Cox proportional hazards regression model comparing the risk of COVID-19 illness (coded as 1 for hospitalised or 0 for infected but not hospitalised) among HCWs. If there are sufficient cases, various predictors of severity will be explored in either univariate or multivariate analysis. Predictors may include age, presence of comorbidities, and viral load.
Measured: Follow-up period 2020-2023.
Estimated SARS-CoV-2 antibody titre associated with protection
We will compare post-season geometric mean titres between those with asymptomatic and symptomatic infections. We will attempt to establish serological correlates of protection for SARS-CoV-2, using a Bayesian implementation of logistic regression that we have used for influenza cohort studies.
Measured: Follow-up period 2020-2023.
Estimated SARS-CoV-2 antibody kinetics over time
Sera collected more frequently will be assessed for antibody titre and the titres compared over time. Geometric mean titres will be calculated and plotted to allow visual inspection of the antibody kinetics, overall and within groups (e.g. age groups, severity of infection). The mean rate of decay will be calculated using linear regression. Because little is known about the decay kinetics, various models will be explored to identify the model with best fit, based on visual inspection of the data and model fitting diagnostics.
Viral load will be included in analyses comparing asymptomatic, mild and severe infections. If possible we will explore the interactions of viral load with demographic (e.g. age) or medical (e.g. heart disease) characteristics.
Measured: Bloods on day 3, day 7, day 14-21, day 30 post infection and end of season. Daily swabs during symptomatic infection to two days post resolution of symptoms. Follow-up period 2020-2023.
Identification of key behavioural drivers of transmission
Using social contacts data, we will attempt to infer the transmission dynamics for our healthcare worker (HCW) participants between each round of sample collection. We will use mathematical models social mixing data with infection risk to untangle specific behaviours/contact scaling that may be driving transmission. These models may be extended to include genetic sequencing data, which has been previously used to reconstruct transmission clusters.
Measured: Follow-up period 2020-2023.
Estimated duration of viral shedding and viral load in SARS-CoV-2 infection over time
We will estimate the average duration of viral shedding and viral load over time and correlation with severity.
Measured: During symptomatic infection to two days post resolution of symptoms. Follow-up period 2020-2023.
Enumeration of SARS-CoV-2-reactive B and T cells and identification of dominant epitopes
Mean antibody concentration will be calculated in innate immune responses.
Measured: Bloods on day 3, day 7, day 14-21, day 30 post infection and end of season. Follow-up period 2020-2023.
Gene expression
Identification of genes that are differentially expressed on day 7 compared to day 0 for each vaccine formulation, focusing on innate immune associated genes.
Measured: Changes from day 0 to day 7 post vaccination. Follow-up period 2020-2023.
Enumeration of SARS-CoV-2-reactive B and T cells induced by each vaccine formulation
Mean antibody concentration will be calculated and compared for vaccine groups (Comirnaty vs Vaxzevria vaccine).
Measured: Specific B and T cells detected at day 14-21 post vaccine schedule completion versus day 0. Follow-up period 2020-2023.
Seroconversion of SARS-CoV-2 serum antibody titres induced by each vaccine formulation
Seroconversion post-vaccination will be calculated and compared between vaccine groups by logistic regression (Comirnaty vs Vaxzevria vaccine).
Measured: At day 14-21 post vaccine schedule completion. Follow-up period 2020-2023.
Fold changes in innate immune cells and in vaccine specific B and T cells
Antibody levels will be correlated with fold changes in innate immune cells and in vaccine specific B and T cells in each vaccine formulation (Comirnaty vs Vaxzevria vaccine).
Measured: Vaccine specific B and T cells detected at day 14-21 post vaccine schedule completion versus day 0. Follow-up period 2020-2023.
Comparison of antibody (and B and T cell) responses induced against COVID-19 and influenza vaccines among participants who received COVID-19 versus influenza vaccine first or who were co-administered both vaccines.
Mean antibody concentration will be calculated and compared for vaccine groups (CoVax vs influenza vaccine). Seroconversion post-vaccination will be calculated and compared between vaccine groups by logistic regression.
Measured: Antibody levels will be correlated with fold changes in innate immune cells and in vaccine specific B and T cells detected at day 14-21 post vaccine schedule completion versus day 0. Follow-up period 2020-2023.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted8 Nov 2021
- Study start2 Apr 2020
- Primary completion30 Jun 2025 (estimated)
- Study completion30 Jun 2025 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (2)Papers the sponsor has linked to this study.
- Other trials for Influenza, HumanStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 1,500 participants (estimated)
Sponsor and investigators
- Lead sponsor
- University of Melbourne
- Sponsor type
- University, hospital or other
- Collaborators
- The University of Queensland, Sydney Children's Hospitals Network, The Alfred, University of Adelaide, The University of Western Australia, London School of Hygiene and Tropical Medicine, University of Newcastle, Australia
- Responsible party
- Sponsor
- Investigators
- Sheena Sullivan, MPH, PhD, Principal investigator, University of MelbourneAnnette Fox, PhD, Principal investigator, University of MelbourneAdam Kucharski, MMath, PhD, Principal investigator, London School of Hygiene and Tropical Medicine
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05110911
- Sponsor's protocol ID
- 1R01AI41534
- Status last verified
- Mar 2025
- First submitted
- 27 Oct 2021
- Last updated
- 1 Apr 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: Sharing original data: The proposed study will collect demographic and clinical information, as well as blood and respiratory specimens from participants. Because we will be conducting longitudinal follow-up, we will be collecting identifiable information. Any data shared will be stripped of identifiers prior to release for sharing. However, there remains the possibility of deductive disclosure of participants with unusual characteristics. Thus, data will only be shared with new collaborators under a data-sharing agreement that provides for: (1) a commitment to using the data only for research purposes and not to identify any individual participant; (2) a commitment to securing the data using appropriate computer technology; and (3) a commitment to destroying or returning the data after analyses are completed.
Publications
Hodgson D, Liu Y, Carolan L, Mahanty S, Subbarao K, Sullivan SG, Fox A, Kucharski A. Memory B cell proliferation drives differences in neutralising responses between ChAdOx1 and BNT162b2 SARS-CoV-2 vaccines. Front Immunol. 2025 Mar 24;16:1487066. doi: 10.3389/fimmu.2025.1487066. eCollection 2025.
PubMed 40196126Liu Y, Sanchez-Ovando S, Carolan L, Dowson L, Khvorov A, Jessica Hadiprodjo A, Tseng YY, Delahunty C, Khatami A, Macnish M, Dougherty S, Hagenauer M, Riley KE, Jadhav A, Harvey J, Kaiser M, Mathew S, Hodgson D, Leung V, Subbarao K, Cheng AC, Macartney K, Koirala A, Marshall H, Clark J, Blyth CC, Wark P, Kucharski AJ, Sullivan SG, Fox A. Superior immunogenicity of mRNA over adenoviral vectored COVID-19 vaccines reflects B cell dynamics independent of anti-vector immunity: Implications for future pandemic vaccines. Vaccine. 2023 Nov 22;41(48):7192-7200. doi: 10.1016/j.vaccine.2023.10.034. Epub 2023 Oct 28.
PubMed 37903679
Study at a glance
From the registry record, last updated by the sponsor on 1 Apr 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Does Repeat Influenza Vaccination Constrain Influenza Immune Responses and Protection
- ClinicalTrials.gov ID
- NCT05110911
- Acronym / sponsor ID
- 1R01AI41534
- Conditions
- Influenza, Human, SARS-CoV-2 Infection
- Keywords
- Vaccine Response Impaired, Influenza, Human, Health Personnel, Influenza Vaccines, SARS-CoV-2 Infection, Immunologic Memory, Vaccination
- Study type
- Observational
- Recruitment status
- Active, not recruiting
- Enrolment
- 1,500 participants (estimated)
- Lead sponsor
- University of MelbourneUniversity, hospital or other
- Collaborators
- The University of Queensland, Sydney Children's Hospitals Network, The Alfred, University of Adelaide, The University of Western Australia, London School of Hygiene and Tropical Medicine, University of Newcastle, Australia
- Study start
- 2 Apr 2020 (actual)
- Primary completion
- 30 Jun 2025 (estimated)
- Study completion
- 30 Jun 2025 (estimated)
- First posted
- 8 Nov 2021 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
The objectives of this study are to understand the long-term consequences of repeated annual influenza vaccination among healthcare workers (HCWs) and to use statistical and mathematical modelling to elucidate the immunological processes that underlie vaccination responses and their implications for vaccination effectiveness. These objectives will be achieved by pursuing three specific aims:
- To study the immunogenicity and effectiveness of influenza vaccination by prior vaccination experience
- To characterize immunological profiles associated with vaccination and infection
- To evaluate the impact of immunity on vaccination effectiveness.
Under Aim 1, a cohort of hospital workers will be recruited and followed for up to 4 years to assess their pre- and post-vaccination and post-season antibody responses, and their risk of influenza infection. These outcomes will be compared by vaccination experience, classified as frequently vaccinated (received ≥3 vaccines in the past 5 years), infrequently vaccinated (<3 vaccinations in past 5 years), vaccinated once, vaccine naïve and unvaccinated.
In Aim 2, intensive cellular and serological assessments will be conducted to dissect the influenza HA-reactive B cell and antibody response, and build antibody landscapes that typify the different vaccination groups.
In Aim 3, the data generated in Aims 1 and 2 will be used to develop a mathematical model that considers prior infection, vaccination history, antibody kinetics, and antigenic distance to understand the effects of repeated vaccination on vaccine effectiveness.
Completion of the proposed research will provide evidence to inform decisions about continued support for influenza vaccination programs among HCWs and general policies for annual influenza vaccination, as well as much needed clarity about the effects of repeated vaccination.
In March-April 2020 pursuant to the SARS-CoV-2 global pandemic an administrative supplement added a SARS-CoV-2 protocol addendum for follow-up of COVID-19 infections amongst our HCW participant cohort.
The following objectives were added:
- To estimate risk factors and correlates of protection for SARS-CoV-2 infection amongst HCW
- To characterize viral kinetics and within-host viral dynamics of SARS-CoV-2 infecting HCW
- To characterize immunological profiles following infection by SARS-CoV-2
- To characterize immunological profiles following vaccination for SARS-CoV-2.
Detailed description
Over 140 million Americans are among the more than 500 million people who receive influenza vaccines annually. An important subgroup are healthcare workers (HCWs) for whom vaccination is recommended, and sometimes mandated, to protect themselves and vulnerable patients from influenza infection. However, there have been no large, long term studies of HCWs to support the effectiveness of these policies. HCWs are now a highly vaccinated population, the effects of which are also poorly understood. Mounting evidence suggests antibody responses to vaccination can be attenuated with repeated vaccination, which is corroborated by reports of poor vaccine effectiveness among the repeatedly vaccinated. Thus, there is a compelling need to directly evaluate HCW vaccination programs. The long term goal is to improve the efficient and effective use of influenza vaccines.
The specific objectives of this study are to understand the long-term consequences of repeated annual influenza vaccination among HCWs and to use statistical and mathematical modeling to elucidate the immunological processes that underlie vaccination responses and their implications for vaccination effectiveness. These objectives will be achieved by pursuing three specific aims:
- To study the immunogenicity and effectiveness of influenza vaccination by prior vaccination experience
- To characterize immunological profiles associated with vaccination and infection
- To evaluate the impact of immunity on vaccination effectiveness.
Under Aim 1, a cohort of hospital workers will be recruited and followed for up to 4 years to assess their pre- and post-vaccination and post-season antibody responses, and their risk of influenza infection. These outcomes will be compared by vaccination experience, classified as frequently vaccinated (received ≥3 vaccines in the past 5 years), infrequently vaccinated (<3 vaccinations in past 5 years), vaccinated once, vaccine naïve and unvaccinated.
In Aim 2, intensive cellular and serological assessments will be conducted to dissect the influenza HA-reactive B cell and antibody response, and build antibody landscapes that typify the different vaccination groups.
In Aim 3, the data generated in Aims 1 and 2 will be used to develop a mathematical model that considers prior infection, vaccination history, antibody kinetics, and antigenic distance to understand the effects of repeated vaccination on vaccine effectiveness. This approach is innovative because it will provide insights into the effect of complex immunological dynamics on infection outcomes, thereby representing a novel departure from previous studies, which have ignored these difficult-to-measure processes. Completion of the proposed research will provide evidence to inform decisions about continued support for influenza vaccination programs among HCWs and general policies for annual influenza vaccination, as well as much needed clarity about the effects of repeated vaccination.
In March-April 2020 pursuant to the SARS-CoV-2 global pandemic an administrative supplement added a SARS-CoV-2 protocol addendum for follow-up of COVID-19 infections amongst our HCW participant cohort.
The following objectives were added under the supplement IRB application:
- To estimate risk factors and correlates of protection for SARS-CoV-2 infection amongst HCW
- To characterize viral kinetics and within-host viral dynamics of SARS-CoV-2 infecting HCW
- To characterize immunological profiles following infection by SARS-CoV-2
- To characterize immunological profiles following vaccination for SARS-CoV-2.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Healthcare Workers | – | Biological: Influenza vaccination: Fluarix Tetra, Vaxigrip Tetra, Fluquadri, Fluad Quad, Afluia Quad, Flucelvax Quad, Biological: SARS-CoV-2 vaccination: Comirnaty or VaxzevriaEligible participants will be recruited from 1 of 6 participating hospitals in Australia and will meet the following criteria: personnel (including staff, honorary staff, students and volunteers) located at a participating hospital or healthcare service at the time of recruitment who would be eligible for the hospital's free vaccination programme; be aged ≥18 years old and ≤60 years old; have a mobile phone that can receive and send SMS messages; willing and able to provide blood samples; available for follow-up over the next 7 months; able and willing to complete the informed consent process. There are no restrictions on the type of healthcare worker (HCW) that can be recruited into the study in terms of their job role. HCW will be any hospital staff, including clinical, research, administrative and support staff. |
Who may qualify
- Ages
- 18 to 60 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult
- Study population
- Healthcare workers (including staff, honorary staff, students and volunteers) from six participating hospitals (or healthcare services) who are eligible for the hospitals' free vaccination programmes, at the time of recruitment.
Key inclusion criteria (8 listed)
- Eligible participants will be recruited from 1 of 6 participating hospitals and will meet the following criteria:
- Personnel (including staff, honorary staff, students and volunteers) located at a participating hospital or healthcare service at the time of recruitment who would be eligible for the hospital's free vaccination programme
- Be aged ≥18 years old and ≤60 years old;
- Have a mobile phone that can receive and send SMS messages;
- Willing and able to provide blood samples;
Key exclusion criteria (2 listed)
- Immunosuppressive treatment (including systemic corticosteroids) within the past 6 months;
- Personnel for whom vaccination is contraindicated at the time of recruitment.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Influenza vaccination: Fluarix Tetra, Vaxigrip Tetra, Fluquadri, Fluad Quad, Afluia Quad, Flucelvax QuadInfluenza vaccine made available to healthcare workers at the participating healthcare sites, as part of their free vaccination campaigns for healthcare workers. | Biological | Healthcare Workers |
| SARS-CoV-2 vaccination: Comirnaty or VaxzevriaSARS-CoV-2 vaccine made available to healthcare workers at the participating healthcare sites, as part of their free vaccination campaigns for healthcare workers. | Biological | Healthcare Workers |
Primary outcome
Seropositivity post-vaccination (influenza vaccine)
Time frame: Post-vaccination blood draws are at 14-21 days post vaccination. Collected each year 2020-2023 post annual influenza vaccination.
Seropositivity among vaccination groups will be calculated and compared using logistic regression, with seropositivity coded as 1 if the titre ≥40, and 0 if the titre is <40. We will test for trend among vaccination groups, assuming seropositivity will be lowest in the most highly vaccinated.
Seropositivity post-season (influenza vaccine)
Time frame: End of the season blood draws are in October or November each year, at the conclusion of Australia's annual influenza season. Vaccination usually occurs in April or May. Collected each year 2020-2023 post annual influenza season.
Seropositivity among vaccination groups will be calculated and compared using logistic regression, with seropositivity coded as 1 if the titre ≥40, and 0 if the titre is <40. We will test for trend among vaccination groups, assuming seropositivity will be lowest in the most highly vaccinated.
Fold-rise in geometric mean antibody titre (GMT) pre- to post-vaccination
Time frame: Changes from day 0 to day 14-21 post influenza vaccination. Collected each year 2020-2023 pre and post annual influenza vaccination.
The changes in GMT from pre- to post-vaccination. Seroconversion is defined as samples with 4-fold increases in hemagglutination inhibition (HI) titre.
Fold-change in geometric mean antibody titre (GMT) post-vaccination to post-season
Time frame: Changes from day 14-21 to post-season. Influenza season in Australia is approximately May to November. Pre-vaccination to post-season is approximately April or May to October or November each year. Collected each year 2020-2023.
The changes in GMT from post-vaccination to post-season.
Seroconversion fraction post-vaccination
Time frame: Changes from day 0 to day 14-21 post influenza vaccination. Collected each year 2020-2023 pre and post annual influenza vaccination.
The proportion of samples with 4-fold increases in hemagglutination inhibition (HI) titre. Seroconversion post-vaccination will be calculated and compared among vaccination groups by logistic regression, with seroconversion coded as 1 if the fold-rise in titre is ≥4 and 0 if the fold-rise in titre is <4. We will test for trend, assuming seroconversion will be lowest in the most highly vaccinated.
24 secondary outcomes
Healthcare workers (HCWs) PCR-positive for influenza at the end of each season
Time frame: Influenza season in Australia is approximately May to November. Follow up for PCR-positives from approximately April/May to October/November each year from 2020-2023.
Influenza attack rate at the end of each season
Time frame: Person-time at risk, during influenza season. Influenza season in Australia is approximately May to November. Follow up for PCR-positives from approximately April/May to October/November each year from 2020-2023.
Vaccine efficacy (VE)
Time frame: Person-time at risk, during influenza season. Influenza season in Australia is approximately May to November. Follow up for PCR-positives from approximately April/May to October/November each year from 2020-2023.
Duration of illness (influenza)
Time frame: Days ill, during influenza season. Influenza season in Australia is approximately May to November. Follow up for PCR-positives from approximately April/May to October/November each year from 2020-2023.
Haemagglutinin (HA) antibody landscapes for vaccine-naïve and highly-vaccinated healthcare workers (HCWs)
Time frame: Bloods on day 0, day 7, day 14-21 post influenza vaccination and end of season. Collected each year 2020-2023 pre and post annual influenza vaccination and end of influenza season.
Haemagglutinin (HA) antibody landscapes for infected versus uninfected healthcare workers (HCWs)
Time frame: Bloods on day 7 and day 14-21 post influenza infection. Collected each year 2020-2023 along with pre and post annual influenza vaccination and end of influenza season bloods.
Enumeration of cells
Time frame: Bloods on day 0 and day 14-21 post influenza vaccination and post infection. The key indicator is the frequency of these B cells on day 14 post-vaccination relative to pre-vaccination frequencies. Collected each year 2020-2023.
B cells
Time frame: Blood draws on day 7 post influenza vaccination and post infection. Collected each year 2020-2023.
Quantify biological mechanisms that shape the antibody response
Time frame: Bloods on day 0, day 7, day 14-21 post influenza vaccination, day 7, day 14-21 post infection and end of season. Collected each year 2020-2023.
Estimate protective titres
Time frame: Bloods on day 0, day 7, day 14-21 post influenza vaccination, day 7, day 14-21 post infection and end of season. Collected each year 2020-2023.
Optimal influenza vaccination strategy for healthcare workers (HCWs) under different vaccine availability
Time frame: Bloods on day 0, day 7, day 14-21 post influenza vaccination, day 7, day 14-21 post infection and end of season. Collected each year 2020-2023.
Estimated SARS-CoV-2 attack rates among symptomatic and asymptomatic healthcare workers (HCWs)
Time frame: Follow-up period 2020-2023.
Case-hospitalization risk
Time frame: Follow-up period 2020-2023.
Risk factors for asymptomatic, mild and severe SARS-CoV-2 infection
Time frame: Follow-up period 2020-2023.
Estimated SARS-CoV-2 antibody titre associated with protection
Time frame: Follow-up period 2020-2023.
Estimated SARS-CoV-2 antibody kinetics over time
Time frame: Bloods on day 3, day 7, day 14-21, day 30 post infection and end of season. Daily swabs during symptomatic infection to two days post resolution of symptoms. Follow-up period 2020-2023.
Identification of key behavioural drivers of transmission
Time frame: Follow-up period 2020-2023.
Estimated duration of viral shedding and viral load in SARS-CoV-2 infection over time
Time frame: During symptomatic infection to two days post resolution of symptoms. Follow-up period 2020-2023.
Enumeration of SARS-CoV-2-reactive B and T cells and identification of dominant epitopes
Time frame: Bloods on day 3, day 7, day 14-21, day 30 post infection and end of season. Follow-up period 2020-2023.
Gene expression
Time frame: Changes from day 0 to day 7 post vaccination. Follow-up period 2020-2023.
Enumeration of SARS-CoV-2-reactive B and T cells induced by each vaccine formulation
Time frame: Specific B and T cells detected at day 14-21 post vaccine schedule completion versus day 0. Follow-up period 2020-2023.
Seroconversion of SARS-CoV-2 serum antibody titres induced by each vaccine formulation
Time frame: At day 14-21 post vaccine schedule completion. Follow-up period 2020-2023.
Fold changes in innate immune cells and in vaccine specific B and T cells
Time frame: Vaccine specific B and T cells detected at day 14-21 post vaccine schedule completion versus day 0. Follow-up period 2020-2023.
Comparison of antibody (and B and T cell) responses induced against COVID-19 and influenza vaccines among participants who received COVID-19 versus influenza vaccine first or who were co-administered both vaccines.
Time frame: Antibody levels will be correlated with fold changes in innate immune cells and in vaccine specific B and T cells detected at day 14-21 post vaccine schedule completion versus day 0. Follow-up period 2020-2023.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 1 Apr 2025.
- Derived from this study: PubMed 40196126Hodgson D, Liu Y, Carolan L, Mahanty S, Subbarao K, Sullivan SG, Fox A, Kucharski A. Memory B cell proliferation drives differences in neutralising responses between ChAdOx1 and BNT162b2 SARS-CoV-2 vaccines. Front Immunol. 2025 Mar 24;16:1487066. doi: 10.3389/fimmu.2025.1487066. eCollection 2025.
- Derived from this study: PubMed 37903679Liu Y, Sanchez-Ovando S, Carolan L, Dowson L, Khvorov A, Jessica Hadiprodjo A, Tseng YY, Delahunty C, Khatami A, Macnish M, Dougherty S, Hagenauer M, Riley KE, Jadhav A, Harvey J, Kaiser M, Mathew S, Hodgson D, Leung V, Subbarao K, Cheng AC, Macartney K, Koirala A, Marshall H, Clark J, Blyth CC, Wark P, Kucharski AJ, Sullivan SG, Fox A. Superior immunogenicity of mRNA over adenoviral vectored COVID-19 vaccines reflects B cell dynamics independent of anti-vector immunity: Implications for future pandemic vaccines. Vaccine. 2023 Nov 22;41(48):7192-7200. doi: 10.1016/j.vaccine.2023.10.034. Epub 2023 Oct 28.
- Individual participant dataSharing planned: Yes. Sharing original data: The proposed study will collect demographic and clinical information, as well as blood and respiratory specimens from participants. Because we will be conducting longitudinal follow-up, we will be collecting identifiable information. Any data shared will be stripped of identifiers prior to release for sharing. However, there remains the possibility of deductive disclosure of participants with unusual characteristics. Thus, data will only be shared with new collaborators under a data-sharing agreement that provides for: (1) a commitment to using the data only for research purposes and not to identify any individual participant; (2) a commitment to securing the data using appropriate computer technology; and (3) a commitment to destroying or returning the data after analyses are completed.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Sheena Sullivan, MPH, PhD principal investigator
University of Melbourne
Annette Fox, PhD principal investigator
University of Melbourne
Adam Kucharski, MMath, PhD principal investigator
London School of Hygiene and Tropical Medicine
6 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Influenza, Human and SARS-CoV-2 Infection, run by University of Melbourne at 6 sites in Australia.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 8 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: under way, not looking for participants, as of the sponsor's last update on 1 Apr 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 6 sites in Australia. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Seropositivity post-vaccination (influenza vaccine) (time frame: Post-vaccination blood draws are at 14-21 days post vaccination. Collected each year 2020-2023 post annual influenza vaccination.). The study lists 5 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT05110911, which also lists 2 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 1 Apr 2025.