W. T. Harvey

This paper uses a Bayesian model to identify genetic changes in influenza A(H3N2) viruses that drive antigenic drift by incorporating protein structural data to improve variable selection accuracy.

The paper identifies spike mutations that adapt SARS-CoV-2 to mustelid hosts and assesses their impact on human infectivity and antigenicity.

This study identifies genetic mutations in H9N2 influenza viruses that influence their receptor-binding preferences and zoonotic potential by altering their affinity for human-like or avian receptors.

This study integrates patient and whole genome sequencing data to analyze the epidemiology of seasonal influenza A(H3N2) viruses, finding that reassortant viruses are associated with severe cases and later seasonality.