1. Epidemiology and Global Health
  2. Microbiology and Infectious Disease
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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
Research Article
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Cite this article as: eLife 2020;9:e50060 doi: 10.7554/eLife.50060


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
    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.


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.


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.

Reviewing Editor

  1. Ben S Cooper, Mahidol University, Thailand

Publication 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)


© 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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Further reading

    1. Epidemiology and Global Health
    2. Microbiology and Infectious Disease
    Mark Ferris et al.
    Research Advance Updated


    Respiratory protective equipment recommended in the UK for healthcare workers (HCWs) caring for patients with COVID-19 comprises a fluid-resistant surgical mask (FRSM), except in the context of aerosol generating procedures (AGPs). We previously demonstrated frequent pauci- and asymptomatic severe acute respiratory syndrome coronavirus 2 infection HCWs during the first wave of the COVID-19 pandemic in the UK, using a comprehensive PCR-based HCW screening programme (Rivett et al., 2020; Jones et al., 2020).


    Here, we use observational data and mathematical modelling to analyse infection rates amongst HCWs working on ‘red’ (coronavirus disease 2019, COVID-19) and ‘green’ (non-COVID-19) wards during the second wave of the pandemic, before and after the substitution of filtering face piece 3 (FFP3) respirators for FRSMs.


    Whilst using FRSMs, HCWs working on red wards faced an approximately 31-fold (and at least fivefold) increased risk of direct, ward-based infection. Conversely, after changing to FFP3 respirators, this risk was significantly reduced (52–100% protection).


    FFP3 respirators may therefore provide more effective protection than FRSMs for HCWs caring for patients with COVID-19, whether or not AGPs are undertaken.


    Wellcome Trust, Medical Research Council, Addenbrooke’s Charitable Trust, NIHR Cambridge Biomedical Research Centre, NHS Blood and Transfusion, UKRI.

    1. Epidemiology and Global Health
    Andria Mousa et al.
    Research Article

    Background: Transmission of respiratory pathogens such as SARS-CoV-2 depends on patterns of contact and mixing across populations. Understanding this is crucial to predict pathogen spread and the effectiveness of control efforts. Most analyses of contact patterns to date have focussed on high-income settings.

    Methods: Here, we conduct a systematic review and individual-participant meta-analysis of surveys carried out in low- and middle-income countries and compare patterns of contact in these settings to surveys previously carried out in high-income countries. Using individual-level data from 28,503 participants and 413,069 contacts across 27 surveys we explored how contact characteristics (number, location, duration and whether physical) vary across income settings.

    Results: Contact rates declined with age in high- and upper-middle-income settings, but not in low-income settings, where adults aged 65+ made similar numbers of contacts as younger individuals and mixed with all age-groups. Across all settings, increasing household size was a key determinant of contact frequency and characteristics, with low-income settings characterised by the largest, most intergenerational households. A higher proportion of contacts were made at home in low-income settings, and work/school contacts were more frequent in high-income strata. We also observed contrasting effects of gender across income-strata on the frequency, duration and type of contacts individuals made.

    Conclusions: These differences in contact patterns between settings have material consequences for both spread of respiratory pathogens, as well as the effectiveness of different non-pharmaceutical interventions.

    Funding: This work is primarily being funded by joint Centre funding from the UK Medical Research Council and DFID (MR/R015600/1).