ReviewHuman vaccines & immunotherapeutics2018
Models for predicting the evolution of influenza to inform vaccine strain selection.
Review in Human vaccines & immunotherapeutics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.
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.
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.
Who cites it
40 citing papers in PubMed, 75 citations in OpenAlex.
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- Multi-View Transformers for Structure-Aware HA-NA Drift Risk Scoring and Mutation Hotspot Mapping.Viruses · 2026Article
- Beyond alarmism: what Australia's influenza season really tells us about Italy.Pathogens and global health · 2026Article
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- Forecasting Influenza Epidemics and Pandemics in the Age of AI and Machine Learning.Reviews in medical virology · 2026Review
- Low effectiveness of influenza vaccines vis-à-vis mechanism of protection by vaccines - potential causes and recommendations to improve control of influenza.Frontiers in immunology · 2026Review
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- Structural characterization of influenza group 1 chimeric hemagglutinins as broad vaccine immunogens.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
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- A broad-spectrum multiepitope vaccine against seasonal influenza A and B viruses in mice.EBioMedicine · 2024Article
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- MAIVeSS: streamlined selection of antigenically matched, high-yield viruses for seasonal influenza vaccine production.Nature communications · 2024Article
- Insight into Antiviral Activity of Ag/TiOInternational journal of nanomedicine · 2024Article
- Characterisation of novel influenza-derived HLA-B*18:01-restricted epitopes.Clinical & translational immunology · 2024Article
- Fighting flu: novel CD8Clinical & translational immunology · 2024Review
- Influenza vaccine: a review on current scenario and future prospects.Journal, genetic engineering & biotechnology · 2023Review
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- Predicting evolutionary outcomes through the probability of accessing sequence variants.Science advances · 2023Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Influenza vaccine composition is reviewed before every flu season because influenza viruses constantly evolve through antigenic changes. To inform vaccine updates, laboratories that contribute to the World Health Organization Global Influenza Surveillance and Response System monitor the antigenic phenotypes of circulating viruses all year round. Vaccine strains are selected in anticipation of the upcoming influenza season to allow adequate time for production. A mismatch between vaccine strains and predominant strains in the flu season can significantly reduce vaccine effectiveness. Models for predicting the evolution of influenza based on the relationship of genetic mutations and antigenic characteristics of circulating viruses may inform vaccine strain selection decisions. We review the literature on state-of-the-art tools and prediction methodologies utilized in modeling the evolution of influenza to inform vaccine strain selection. We then discuss areas that are open for improvement and need further research.
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Registered trials
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.