Estimation of Seasonal Influenza Attack Rates and Antibody Dynamics in Children Using Cross-Sectional Serological Data

J Infect Dis. 2022 May 16;225(10):1750-1754. doi: 10.1093/infdis/jiaa338.

Abstract

Directly measuring evidence of influenza infections is difficult, especially in low-surveillance settings such as sub-Saharan Africa. Using a Bayesian model, we estimated unobserved infection times and underlying antibody responses to influenza A/H3N2, using cross-sectional serum antibody responses to 4 strains in children aged 24-60 months. Among the 242 individuals, we estimated a variable seasonal attack rate and found that most children had ≥1 infection before 2 years of age. Our results are consistent with previously published high attack rates in children. The modeling approach highlights how cross-sectional serological data can be used to estimate epidemiological dynamics.

Keywords: Bayesian model; The Gambia; childhood infection; influenza; serology.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Antibodies, Viral
  • Bayes Theorem
  • Child
  • Child, Preschool
  • Cross-Sectional Studies
  • Humans
  • Incidence
  • Influenza A Virus, H3N2 Subtype
  • Influenza, Human* / epidemiology
  • Seasons

Substances

  • Antibodies, Viral