Stochastic Processes Are Key Determinants of Short-Term Evolution in Influenza A Virus

TLDR

Influenza A virus evolution is central to surveillance and control, yet while antigenic drift drives seasonal change, the within‑season processes shaping diversity remain unclear. The study seeks to improve vaccine strain prediction by emphasizing intensive surveillance, whole‑genome sequencing, and phenotypic analysis. Phylogenetic analysis of 413 H3N2 genomes revealed abundant diversity driven mainly by seasonal importation of divergent clades and reassortment, with limited positive selection at key antigenic sites, indicating that stochastic migration and reassortment, rather than adaptive evolution, dominate short‑term influenza dynamics.

Abstract

Understanding the evolutionary dynamics of influenza A virus is central to its surveillance and control. While immune-driven antigenic drift is a key determinant of viral evolution across epidemic seasons, the evolutionary processes shaping influenza virus diversity within seasons are less clear. Here we show with a phylogenetic analysis of 413 complete genomes of human H3N2 influenza A viruses collected between 1997 and 2005 from New York State, United States, that genetic diversity is both abundant and largely generated through the seasonal importation of multiple divergent clades of the same subtype. These clades cocirculated within New York State, allowing frequent reassortment and generating genome-wide diversity. However, relatively low levels of positive selection and genetic diversity were observed at amino acid sites considered important in antigenic drift. These results indicate that adaptive evolution occurs only sporadically in influenza A virus; rather, the stochastic processes of viral migration and clade reassortment play a vital role in shaping short-term evolutionary dynamics. Thus, predicting future patterns of influenza virus evolution for vaccine strain selection is inherently complex and requires intensive surveillance, whole-genome sequencing, and phenotypic analysis.