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

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...

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Detalles Bibliográficos
Autores principales: Minter, Amanda, Hoschler, Katja, Jagne, Ya Jankey, Sallah, Hadijatou, Armitage, Edwin, Lindsey, Benjamin, Hay, James A, Riley, Steven, de Silva, Thushan I, Kucharski, Adam J
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9113438/
https://www.ncbi.nlm.nih.gov/pubmed/32556290
http://dx.doi.org/10.1093/infdis/jiaa338
Descripción
Sumario: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.