We study how the host adaptive immune response coevolves with pathogens, especially in ways relevant to epidemiological and evolutionary forecasting, vaccine design, and pathogen diversity. Our work is computational, and we collaborate closely with immunologists and epidemiologists.
We find that strong immune memory biases may make influenza, SARS-CoV-2, and other pathogens more likely to diversify, in contrast to prevailing theory that ignores these biases.
Jan. 5, 2024
We find that measuring neutralizing antibodies at the population level can help predict which clade of influenza will dominate and in whom. We also find antibody targeting of flu diversifies with age.
Oct. 27, 2023
High-throughput sequencing-based neutralization assay reveals how repeated vaccinations impact titers to recent human H1N1 influenza strains in bioRxiv (2024)
A speed limit on serial strain replacement from original antigenic sin in bioRxiv (2024)
Measures of population immunity can predict the dominant clade of influenza A (H3N2) and reveal age-associated differences in susceptibility and specificity in medRxiv (2023)
Germline-encoded specificities and the predictability of the B cell response in PLOS Pathogens (2023)