Evidence map›Paper›PMID 32556290›Full record

ArticleThe Journal of infectious diseases2022

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

Amanda Minter, Katja Hoschler, Ya Jankey Jagne, Hadijatou Sallah, Edwin Armitage, Benjamin Lindsey, James A Hay, Steven Riley, Thushan I de Silva, Adam J Kucharski

Abstract read
In one paragraph

Article in The Journal of infectious diseases, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

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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

10 authors.

Amanda MinterCentre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom.ORCID 0000-0003-1171-5688
Katja HoschlerRespiratory Virus Reference Department, Public Health England, London, United Kingdom.
Ya Jankey JagneMedical Research Council Unit The Gambia at the London School of Hygiene & Tropical Medicine, Banjul, The Gambia.
Hadijatou SallahMedical Research Council Unit The Gambia at the London School of Hygiene & Tropical Medicine, Banjul, The Gambia.
Edwin ArmitageMedical Research Council Unit The Gambia at the London School of Hygiene & Tropical Medicine, Banjul, The Gambia.
Benjamin LindseyMedical Research Council Unit The Gambia at the London School of Hygiene & Tropical Medicine, Banjul, The Gambia.
James A HayMRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom.
Steven RileyMRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom.
Thushan I de SilvaMedical Research Council Unit The Gambia at the London School of Hygiene & Tropical Medicine, Banjul, The Gambia.
Adam J KucharskiCentre for the Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, United Kingdom.

Funding

Medical Research Council MC_PC_19012Medical Research Council MR/J008761/1Medical Research Council MR/R015600/1Wellcome Trust 200861/Z/16/ZWellcome Trust 206250/Z/17/Z
6 · The paper itself

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.

Indexed as

Influenza, HumanAntibodies, ViralBayes TheoremChildChild, PreschoolCross-Sectional StudiesHumansIncidenceInfluenza A Virus, H3N2 SubtypeSeasonsAntibodies, ViralBayesian modelchildhood infectioninfluenzaserologyThe Gambia

Identifiers

PMID32556290
PMCPMC9113438

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.