PT  - JOURNAL ARTICLE
AU  - Melia E. Bonomo
AU  - Michael W. Deem
TI  - Predicting influenza H3N2 vaccine efficacy from evolution of the dominant epitope
AID  - 10.1101/300665
DP  - 2018 Jan 01
TA  - bioRxiv
PG  - 300665
4099  - http://biorxiv.org/content/early/2018/04/12/300665.short
4100  - http://biorxiv.org/content/early/2018/04/12/300665.full
AB  - We predict vaccine efficacy with a measure of antigenic distance between influenza A(H3N2) and candidate vaccine viruses based on amino acid substitutions in the dominant epitopes. In 2016-2017, our model predicts 19% efficacy compared to 20% observed. This tool assists candidate vaccine selection by predicting human protection against circulating strains.40-word summary of main point Our pepitope model predicts the ability of the influenza vaccine to reduce the A(H3N2) disease attack rate, with an r^2=0.77. This fast, sequence-based method compliments strain-to-strain antigenic comparisons from ferret models and provides antigenic comparisons for all circulating sequences.