Evidence map›Paper›PMID 32970783›Full record

ReviewPLoS pathogens2020

Beyond clinical trials: Evolutionary and epidemiological considerations for development of a universal influenza vaccine.

Cécile Viboud, Katelyn Gostic, Martha I Nelson, Graeme E Price, Amanda Perofsky, Kaiyuan Sun, Nídia Sequeira Trovão, Benjamin J Cowling, Suzanne L Epstein, David J Spiro

Open access · goldAbstract readReview
In one paragraph

Review in PLoS pathogens, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
3.2field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

20 citing papers in PubMed, 35 citations in OpenAlex.

  1. Review
  2. The speed of vaccination rollout and the risk of pathogen adaptation.Journal of the Royal Society, Interface · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 4 institutions in 2 countries.

Cécile ViboudDivision of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States.ORCID 0000-0003-3243-4711
Katelyn GosticDept. of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, California, United States.
Martha I NelsonDivision of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States.
Graeme E PriceCenter for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring, Maryland, United States.ORCID 0000-0002-0190-3354
Amanda PerofskyDivision of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States.ORCID 0000-0001-7341-9193
Kaiyuan SunDivision of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States.
Nídia Sequeira TrovãoDivision of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States.
Benjamin J CowlingWorld Health Organization Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, The University of Hong Kong, Hong Kong Special Administrative Region, China.ORCID 0000-0002-6297-7154
Suzanne L EpsteinCenter for Biologics Evaluation and Research, Food and Drug Administration, Silver Spring, Maryland, United States.ORCID 0000-0002-6311-6890
David J SpiroDivision of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States.ORCID 0000-0002-8158-7696
National Institutes of Health · USCenter for Biologics Evaluation and Research · USUniversity of California, Los Angeles · USUniversity of Hong Kong · HK

Funding

Epidemiological impacts of broadly protective childhood HA imprinting on seasonal and pandemic influenzaF31AI134017 · NIAID · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI GOSTIC, KATELYN MARIE · 2017 to 2018
$76k
NIAID NIH HHS F31 AI134017NIAID NIH HHS HHSN272201400008C
6 · The paper itself

Abstract

The prospect of universal influenza vaccines is generating much interest and research at the intersection of immunology, epidemiology, and viral evolution. While the current focus is on developing a vaccine that elicits a broadly cross-reactive immune response in clinical trials, there are important downstream questions about global deployment of a universal influenza vaccine that should be explored to minimize unintended consequences and maximize benefits. Here, we review and synthesize the questions most relevant to predicting the population benefits of universal influenza vaccines and discuss how existing information could be mined to begin to address these questions. We review three research topics where computational modeling could bring valuable evidence: immune imprinting, viral evolution, and transmission. We address the positive and negative consequences of imprinting, in which early childhood exposure to influenza shapes and limits immune responses to future infections via memory of conserved influenza antigens. However, the mechanisms at play, their effectiveness, breadth of protection, and the ability to "reprogram" already imprinted individuals, remains heavily debated. We describe instances of rapid influenza evolution that illustrate the plasticity of the influenza virus in the face of drug pressure and discuss how novel vaccines could introduce new selective pressures on the evolution of the virus. We examine the possible unintended consequences of broadly protective (but infection-permissive) vaccines on the dynamics of epidemic and pandemic influenza, compared to conventional vaccines that have been shown to provide herd immunity benefits. In conclusion, computational modeling offers a valuable tool to anticipate the benefits of ambitious universal influenza vaccine programs, while balancing the risks from endemic influenza strains and unpredictable pandemic viruses. Moving forward, it will be important to mine the vast amount of data generated in clinical studies of universal influenza vaccines to ensure that the benefits and consequences of these vaccine programs have been carefully modeled and explored.

Indexed as

Antibodies, ViralBiomedical ResearchClinical Trials as TopicHemagglutinin Glycoproteins, Influenza VirusHumansInfluenza A virusInfluenza, HumanInfluenza VaccinesAntibodies, ViralHemagglutinin Glycoproteins, Influenza VirusInfluenza Vaccines

Identifiers

PMID32970783
PMCPMC7514029
OpenAlexW3088285566

What OpenQuestion holds

Textmetadata
LicenceCC0
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.