Predicting Influenza H3N2 Vaccine Efficacy From Evolution of the Dominant Epitope

Clin Infect Dis. 2018 Sep 14;67(7):1129-1131. doi: 10.1093/cid/ciy323.

Abstract

We predict vaccine efficacy with a measure of antigenic distance between influenza A(H3N2) and vaccine viruses based on amino acid substitutions in the dominant epitope. In 2016-2017, our model predicts 19% efficacy compared with 20% observed. This tool assists candidate vaccine selection by predicting human protection against circulating strains.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Antibodies, Viral / immunology
  • Antigens, Viral
  • Evolution, Molecular
  • Humans
  • Immunodominant Epitopes / immunology*
  • Influenza A Virus, H3N2 Subtype
  • Influenza Vaccines / immunology*
  • Influenza, Human / prevention & control*
  • Mathematical Computing
  • Models, Biological

Substances

  • Antibodies, Viral
  • Antigens, Viral
  • Immunodominant Epitopes
  • Influenza Vaccines