Seasonal variation in the age distribution of influenza A cases suggests that factors other than age shape susceptibility to medically attended infection. We ask whether these differences can be partly explained by protection conferred by childhood influenza infection, which has lasting impacts on immune responses to influenza and protection against new influenza A subtypes (phenomena known as original antigenic sin and immune imprinting). Fitting a statistical model to data from studies of influenza vaccine effectiveness (VE), we find that primary infection appears to reduce the risk of medically attended infection with that subtype throughout life. This effect is stronger for H1N1 compared to H3N2. Additionally, we find evidence that VE varies with both age and birth year, suggesting that VE is sensitive to early exposures. Our findings may improve estimates of age-specific risk and VE in similarly vaccinated populations and thus improve forecasting and vaccination strategies to combat seasonal influenza.
Code and data for calculation of imprinting probabilities, vaccination coverage, and model fitting are available on GitHub at https://github.com/cobeylab/FluAImprinting.
Data and code from Earliest infections predict the age distribution of seasonal influenza A casesGitHub repository, cobeylab/FluAImprinting.
- Sarah Cobey
- Philip Arevalo
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Human subjects: Study procedures for the vaccine effectiveness study was approved by the IRB at the Marshfield Clinic Research Institute. Informed consent was obtained from all participants at the time of enrollment into the vaccine effectiveness study. This analysis was subsequently approved by the Marshfield Clinic Research Institute IRB with a waiver of informed consent. The analysis of data was approved by the University of Chicago IRB under protocol number IRB17-1134-CR001.
- Ben S Cooper, Mahidol University, Thailand
© 2020, Arevalo et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.