Evidence map›Paper›PMID 25734701›Full record

ArticlePLoS biology2015

Estimating the life course of influenza A(H3N2) antibody responses from cross-sectional data.

Adam J Kucharski, Justin Lessler, Jonathan M Read, Huachen Zhu, Chao Qiang Jiang, Yi Guan, Derek A T Cummings, Steven Riley

Abstract read
In one paragraph

Article in PLoS biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 107 papers.

0numbers the graph read from it
0cells of the map it votes in
107citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

107 citing papers in PubMed.

  1. Trial
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  5. The ageing immune system and its battle with viruses.The Journal of general virology · 2026
    Review
  6. Article
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  9. mBio · 2026
    Article
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47 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Adam J KucharskiDepartment of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, United Kingdom; MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom.
Justin LesslerDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America.
Jonathan M ReadDepartment of Epidemiology and Population Health, Institute of Infection and Global Health, Faculty of Health and Life Sciences, University of Liverpool, Liverpool, United Kingdom.
Huachen ZhuInternational Institute of Infection and Immunity, Shantou University Medical College, Shantou, Guangdong, China; State Key Laboratory of Emerging Infectious Diseases and Centre of Influenza Research, University of Hong Kong, Hong Kong SAR, China.
Chao Qiang JiangGuangzhou No. 12 Hospital, Guangzhou, Guangdong, China.
Yi GuanInternational Institute of Infection and Immunity, Shantou University Medical College, Shantou, Guangdong, China; State Key Laboratory of Emerging Infectious Diseases and Centre of Influenza Research, University of Hong Kong, Hong Kong SAR, China.
Derek A T CummingsDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America.
Steven RileyMRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom.

Funding

Models for synthesising molecular, clinical and epidemiological data, and translaU01GM110721 · NIGMS · IMPERIAL COLLEGE OF SCIENCE, TECHNOLOGY AND MEDICINE · PI CAUCHEMEZ, SIMON, FERGUSON, NEIL MORRIS · 2014 to 2018
$1.9M
Ecology of Infectious Diseases (EID)-Immune Landscapes of Human Influenza in HousR01TW008246 · FIC · JOHNS HOPKINS UNIVERSITY · PI CUMMINGS, DEREK A · 2008 to 2011
$1.9M
Estimation of Intervention Effects in Influenza OutbreaksK22AI092150 · NIAID · JOHNS HOPKINS UNIVERSITY · PI LESSLER, JUSTIN · 2011 to 2012
$270k
FIC NIH HHS R01 TW008246FIC NIH HHS R01 TW008246-01Medical Research Council MR/J008761/1Medical Research Council MR/K010174/1NIAID NIH HHS K22 AI092150NIAID NIH HHS K22 AI092150-01NIGMS NIH HHS U01 GM110721NIGMS NIH HHS U01 GM110721-01Wellcome TrustWellcome Trust 093488/Z/10/Z
6 · The paper itself

Abstract

The immunity of a host population against specific influenza A strains can influence a number of important biological processes, from the emergence of new virus strains to the effectiveness of vaccination programmes. However, the development of an individual's long-lived antibody response to influenza A over the course of a lifetime remains poorly understood. Accurately describing this immunological process requires a fundamental understanding of how the mechanisms of boosting and cross-reactivity respond to repeated infections. Establishing the contribution of such mechanisms to antibody titres remains challenging because the aggregate effect of immune responses over a lifetime are rarely observed directly. To uncover the aggregate effect of multiple influenza infections, we developed a mechanistic model capturing both past infections and subsequent antibody responses. We estimated parameters of the model using cross-sectional antibody titres to nine different strains spanning 40 years of circulation of influenza A(H3N2) in southern China. We found that "antigenic seniority" and quickly decaying cross-reactivity were important components of the immune response, suggesting that the order in which individuals were infected with influenza strains shaped observed neutralisation titres to a particular virus. We also obtained estimates of the frequency and age distribution of influenza infection, which indicate that although infections became less frequent as individuals progressed through childhood and young adulthood, they occurred at similar rates for individuals above age 30 y. By establishing what are likely to be important mechanisms driving epochal trends in population immunity, we also identified key directions for future studies. In particular, our results highlight the need for longitudinal samples that are tested against multiple historical strains. This could lead to a better understanding of how, over the course of a lifetime, fast, transient antibody dynamics combine with the longer-term immune responses considered here.

Indexed as

Adaptive ImmunityImmunologic MemoryModels, ImmunologicalAdolescentAdultAgedAge DistributionAntibodies, ViralChildChild, PreschoolChinaCross ProtectionCross-Sectional StudiesHumansInfluenza A Virus, H3N2 SubtypeInfluenza, HumanAntibodies, Viral

Identifiers

PMID25734701
PMCPMC4348415

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.