Dataset

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Title of Dataset
Data from: Estimating the Life Course of Influenza A(H3N2) Antibody Responses from Cross-Sectional Data
Author of Dataset
Kucharski, Adam J.1
Lessler, Justin2
Read, Jonathan M.3
Jiang, Chao Qiang5
Cummings, Derek A. T.2
Riley, Steven6
Contact
Kucharski, Adam J.1
Date of Dataset Creation
2015-03-03
Description
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.
Citation
Kucharski, AJ, Lessler, J, Read, JM, Zhu, H, Jiang, CQ, Guan, Y, Cummings, DAT, Riley, S. (2015). Data from: Estimating the Life Course of Influenza A(H3N2) Antibody Responses from Cross-Sectional Data. [Data File]. All relevant data are within the paper and its Supporting Information files. Click on “Linked Publications” to access the publication and access supporting information on figshare at https://figshare.com/articles/_Estimating_the_Life_Course_of_Influenza_A_H3N2_Antibody_Responses_from_Cross_Sectional_Data_/1321633
Subject (RGC Codes)
H2 — Social and Behavioural Sciences — 社會及行為學
  • 4409 — Public Health — 公共衛生
Subject (ANZSRC)
11 — MEDICAL AND HEALTH SCIENCES — 醫學與衛生科學
  • 1117 — PUBLIC HEALTH AND HEALTH SERVICES — 公共衛生
    • 111706 — Epidemiology — 流行病學
Keyword
influenza
strain
individual
antibody titres
lifetime
mechanism
infection
age 30 y
response
Affiliations
  1. London Sch Hyg & Trop Med, Dept Infect Dis Epidemiol, London WC1, England ; Univ London Imperial Coll Sci Technol & Med, Sch Publ Hlth, Dept Infect Dis Epidemiol, MRC Ctr Outbreak Anal & Modelling, London, England
  2. Johns Hopkins Bloomberg Sch Publ Hlth, Dept Epidemiol, Baltimore, MD USA
  3. Univ Liverpool, Fac Hlth & Life Sci, Inst Infect & Global Hlth, Dept Epidemiol & Populat Hlth, Liverpool L69 3BX, Merseyside, England
  4. Shantou Univ, Coll Med, Int Inst Infect & Immun, Shantou, Guangdong, Peoples R China ; Univ Hong Kong, State Key Lab Emerging Infect Dis, Hong Kong, Hong Kong, Peoples R China ; Univ Hong Kong, Influenza Res Ctr, Hong Kong, Hong Kong, Peoples R China
  5. Guangzhou 12 Hosp, Guangzhou, Guangdong, Peoples R China
  6. Univ London Imperial Coll Sci Technol & Med, Sch Publ Hlth, Dept Infect Dis Epidemiol, MRC Ctr Outbreak Anal & Modelling, London, England