Joint visualization of seasonal influenza serology and phylogeny to inform vaccine composition

Abstract

Seasonal influenza vaccines must be updated regularly to account for mutations that allow influenza viruses to escape our existing immunity. A successful vaccine should represent the genetic diversity of recently circulating viruses and induce antibodies that effectively prevent infection by those recent viruses. Thus, linking the genetic composition of circulating viruses and the serological experimental results measuring antibody efficacy is crucial to the vaccine design decision. Historically, genetic and serological data have been presented separately in the form of static visualizations of phylogenetic trees and tabular serological results to identify vaccine candidates. To simplify this decision-making process, we have created an interactive tool for visualizing serological data that has been integrated into Nextstrain’s real-time phylogenetic visualization framework, Auspice. We show how the combined interactive visualizations may be used by decision makers to explore the relationships between complex data sets for both prospective vaccine virus selection and retrospectively exploring the performance of vaccine viruses.

Assessing the Intense Influenza A(H1N1)pdm09 Epidemic and Vaccine Effectiveness in the Post-COVID Season in the Russian Federation

“…It is well known that influenza vaccine effectiveness is highly dependent on the matching of strains in influenza vaccines and actually circulating viruses [ 22 ]. In recent years, many tools have been proposed to contribute to the vaccine selection process including short-term modeling strategies and visualizations [ 4 , 23 , 24 ] but none of them currently can predict the vaccine strains without ongoing global surveillance activities and massive antigenic and genetic analysis work conducted by the WHO CCs and the NICs [ 25 ].…”