RT Journal Article
SR Electronic
T1 Timescales of influenza A/H3N2 antibody dynamics
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 183111
DO 10.1101/183111
A1 Adam J. Kucharski
A1 Derek A. T. Cummings
A1 Steven Riley
YR 2017
UL http://biorxiv.org/content/early/2017/08/31/183111.abstract
AB Human immunity shapes the evolution and impact of novel influenza strains. However, it is challenging to quantify the mechanisms that shape observed immune responses or reliably estimate infection from serology because individuals are infected with multiple strains during their lifetime. Using a Bayesian model of antibody dynamics at different timescales, we explain complex cross-reactive antibody landscapes by inferring participants' histories of infection with serological data from studies in southern China and Vietnam. We show antibody profiles are generated by a short-lived, broadly cross-reactive response that decays to leave a long-term response acting against a narrower range of strains. We also suggest an alternative to seroconversion for the estimation of infection attack rates. Our work provides a general method for elucidating mechanisms of influenza immunity from serological data, and suggests a two-armed immune response to influenza infection consistent with competitive dynamics between acute and convalescent B cell populations.