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Vaccine. 2019 May 27;37(24):3154-3158. doi: 10.1016/j.vaccine.2019.03.068. Epub 2019 May 3.

Modular epitope binding predicts influenza quasispecies dominance and vaccine effectiveness: Application to 2018/19 season.

Author information

1
Department of Physics and Astronomy, Rice University, 6100 Main St, Houston, TX 77005, USA; Center for Theoretical Biological Physics, Rice University, 6100 Main St, Houston, TX 77005, USA. Electronic address: meb16@rice.edu.
2
Weiss School of Natural Sciences, Rice University, 6100 Main St, Houston, TX 77005, USA. Electronic address: ryk4@rice.edu.
3
Department of Physics and Astronomy, Rice University, 6100 Main St, Houston, TX 77005, USA; Center for Theoretical Biological Physics, Rice University, 6100 Main St, Houston, TX 77005, USA; Department of Bioengineering, Rice University, 6100 Main St, Houston, TX 77005, USA. Electronic address: mwdeem@rice.edu.

Abstract

The modular binding sites on the influenza A(H3N2) hemagglutinin protein are under significant pressure to acquire mutations in order to evade human antibody recognition. Analysis of these hemagglutinin epitopes in the strains circulating during 2017/18 and early 2018/19 identified the emergence of a new antigenic cluster that has grown from 4% of circulating strains to 11%. We regressed our module-based antigenic distance, pepitope, with A(H3N2) vaccine effectiveness from recent studies conducted by the US Centers for Disease Control and Prevention (r2 = 0.92), and we used this to estimate that the 2018/19 vaccines will protect against most circulating A(H3N2) strains. The pEpitope model is useful for A(H3N2) influenza vaccine virus selection and development, and it has the potential to aid national or regional regulatory authorities in making geographically localized decisions.

KEYWORDS:

Antigenic distance; Immunity; Mathematical models; Seasonal influenza; Vaccination planning; Vaccine effectiveness

PMID:
31060950
DOI:
10.1016/j.vaccine.2019.03.068
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