Prediction of influenza B vaccine effectiveness from sequence data

Vaccine. 2016 Aug 31;34(38):4610-4617. doi: 10.1016/j.vaccine.2016.07.015. Epub 2016 Jul 26.

Abstract

Influenza is a contagious respiratory illness that causes significant human morbidity and mortality, affecting 5-15% of the population in a typical epidemic season. Human influenza epidemics are caused by types A and B, with roughly 25% of human cases due to influenza B. Influenza B is a single-stranded RNA virus with a high mutation rate, and both prior immune history and vaccination put significant pressure on the virus to evolve. Due to the high rate of viral evolution, the influenza B vaccine component of the annual influenza vaccine is updated, roughly every other year in recent years. To predict when an update to the vaccine is needed, an estimate of expected vaccine effectiveness against a range of viral strains is required. We here introduce a method to measure antigenic distance between the influenza B vaccine and circulating viral strains. The measure correlates well with effectiveness of the influenza B component of the annual vaccine in humans between 1979 and 2014. We discuss how this measure of antigenic distance may be used in the context of annual influenza vaccine design and prediction of vaccine effectiveness.

Keywords: Antigenic distance; Influenza B.

MeSH terms

  • Antigens, Viral / immunology*
  • Cluster Analysis
  • Epitope Mapping
  • Evolution, Molecular
  • Humans
  • Immunogenicity, Vaccine*
  • Influenza B virus / genetics
  • Influenza B virus / immunology*
  • Influenza Vaccines / therapeutic use*
  • Influenza, Human / prevention & control*
  • RNA, Viral / genetics
  • Sequence Alignment

Substances

  • Antigens, Viral
  • Influenza Vaccines
  • RNA, Viral