Timescales of influenza A/H3N2 antibody dynamics

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. 1 . CC-BY-NC 4.0 International license not peer-reviewed) is the author/funder. It is made available under a The copyright holder for this preprint (which was . http://dx.doi.org/10.1101/183111 doi: bioRxiv preprint first posted online Aug. 31, 2017;