Antigenic drift and subtype interference shape A(H3N2) epidemic dynamics in the United States

Author:

Perofsky Amanda C12ORCID,Huddleston John3,Hansen Chelsea12,Barnes John R4,Rowe Thomas4,Xu Xiyan4,Kondor Rebecca4,Wentworth David E4,Lewis Nicola5,Whittaker Lynne5,Ermetal Burcu5,Harvey Ruth5,Galiano Monica5,Daniels Rodney Stuart5,McCauley John W5,Fujisaki Seiichiro6,Nakamura Kazuya6,Kishida Noriko6,Watanabe Shinji6,Hasegawa Hideki6,Sullivan Sheena G7,Barr Ian G7,Subbarao Kanta7,Krammer Florian89,Bedford Trevor231011,Viboud Cécile1

Affiliation:

1. Fogarty International Center, National Institutes of Health

2. Brotman Baty Institute for Precision Medicine, University of Washington

3. Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center

4. Virology Surveillance and Diagnosis Branch, Influenza Division, National Center for Immunization and Respiratory Diseases (NCIRD), Centers for Disease Control and Prevention (CDC)

5. WHO Collaborating Centre for Reference and Research on Influenza, Crick Worldwide Influenza Centre, The Francis Crick Institute

6. Influenza Virus Research Center, National Institute of Infectious Diseases

7. WHO Collaborating Centre for Reference and Research on Influenza, The Peter Doherty Institute for Infection and Immunity, Department of Microbiology and Immunology, The University of Melbourne, The Peter Doherty Institute for Infection and Immunity

8. Center for Vaccine Research and Pandemic Preparedness (C-VaRPP), Icahn School of Medicine at Mount Sinai

9. Department of Pathology

10. Department of Genome Sciences, University of Washington

11. Howard Hughes Medical Institute

Abstract

Influenza viruses continually evolve new antigenic variants, through mutations in epitopes of their major surface proteins, hemagglutinin (HA) and neuraminidase (NA). Antigenic drift potentiates the reinfection of previously infected individuals, but the contribution of this process to variability in annual epidemics is not well understood. Here we link influenza A(H3N2) virus evolution to regional epidemic dynamics in the United States during 1997—2019. We integrate phenotypic measures of HA antigenic drift and sequence-based measures of HA and NA fitness to infer antigenic and genetic distances between viruses circulating in successive seasons. We estimate the magnitude, severity, timing, transmission rate, age-specific patterns, and subtype dominance of each regional outbreak and find that genetic distance based on broad sets of epitope sites is the strongest evolutionary predictor of A(H3N2) virus epidemiology. Increased HA and NA epitope distance between seasons correlates with larger, more intense epidemics, higher transmission, greater A(H3N2) subtype dominance, and a greater proportion of cases in adults relative to children, consistent with increased population susceptibility. Based on random forest models, A(H1N1) incidence impacts A(H3N2) epidemics to a greater extent than viral evolution, suggesting that subtype interference is a major driver of influenza A virus infection dynamics, presumably via heterosubtypic cross-immunity. Impact statement: Antigenic drift in influenza’s major surface proteins – hemagglutinin and neuraminidase – contributes to variability in epidemic magnitude across seasons but is less influential than subtype interference in shaping annual outbreaks.

Publisher

eLife Sciences Publications, Ltd

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