Earliest infections predict the age distribution of seasonal influenza A cases

  1. Philip Arevalo  Is a corresponding author
  2. Huong Q McLean
  3. Edward A Belongia
  4. Sarah Cobey
  1. University of Chicago, United States
  2. Marshfield Clinic Research Institute, United States

Abstract

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.

Data availability

Code and data for calculation of imprinting probabilities, vaccination coverage, and model fitting are available on GitHub at https://github.com/cobeylab/FluAImprinting.

The following data sets were generated

Article and author information

Author details

  1. Philip Arevalo

    Ecology and Evolution, University of Chicago, Chicago, United States
    For correspondence
    parevalo@uchicago.edu
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1237-2314
  2. Huong Q McLean

    Center for Clinical Epidemiology and Population Health, Marshfield Clinic Research Institute, Marshfield, United States
    Competing interests
    Huong Q McLean, has received funding from Seqirus, unrelated to this work. The author has no other competing interests to declare.
  3. Edward A Belongia

    Center for Clinical Epidemiology and Population Health, Marshfield Clinic Research Institute, Marshfield, United States
    Competing interests
    No competing interests declared.
  4. Sarah Cobey

    Department of Ecology and Evolutionary Biology, University of Chicago, Chicago, United States
    Competing interests
    No competing interests declared.

Funding

National Institutes of Health (DP2AI117921,HHSN272201400005C)

  • Sarah Cobey

National Institutes of Health (F32AI145177-01)

  • Philip Arevalo

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Ben S Cooper, Mahidol University, Thailand

Ethics

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.

Version history

  1. Received: July 10, 2019
  2. Accepted: June 29, 2020
  3. Accepted Manuscript published: July 7, 2020 (version 1)
  4. Version of Record published: July 17, 2020 (version 2)

Copyright

© 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.

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  1. Philip Arevalo
  2. Huong Q McLean
  3. Edward A Belongia
  4. Sarah Cobey
(2020)
Earliest infections predict the age distribution of seasonal influenza A cases
eLife 9:e50060.
https://doi.org/10.7554/eLife.50060

Share this article

https://doi.org/10.7554/eLife.50060

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