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Influenza Virus: Dealing with a Drifting and Shifting Pathogen
Abstract
Numerous modern technological and scientific advances have changed the vaccine industry. However, nearly 70 years of influenza vaccine usage have passed without substantial changes in the underlying principles of the vaccine. The challenge of vaccinating against influenza lies in the constantly changing nature of the virus itself. Influenza viruses undergo antigenic evolution through antigenic drift and shift in their surface glycoproteins. This has forced frequent updates of vaccine antigens to ensure that the somewhat narrowly focused vaccine-induced immune responses defend against circulating strains. Few vaccine production systems have been developed that can entertain such constant changes. Although influenza virus infection induces long-lived immunologic memory to the same or similar strains, most people do not encounter the same strain repeatedly in their lifespan, suggesting that enhancement of natural immunity is required to improve influenza vaccines. It is clear that transformative change of influenza vaccines requires a rethink of how we immunize. In this study, we review the problems associated with the changing nature of the virus, and highlight some of the approaches being employed to improve influenza vaccines.
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Metadata
- Authors
- Kim, H., Webster, R. G., & Webby, R. J.
- Venue
- Viral Immunology
- Publisher
- SAGE Publications
- Published
- 2018-03
- Volume
- 31
- Issue
- 2
- Pages
- 174-183
- ISSN
- 0882-8245 (ISSN-L)
- 1557-8976
- OpenAlex
- W2786042132
- Cited by
- 419
- References
- 89
- FWCI
- 24.55
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.