Please use this identifier to cite or link to this item: https://doi.org/10.1111/irv.12452
Title: Rethinking thresholds for serological evidence of influenza virus infection
Authors: Zhao, X 
Siegel, K 
Chen, M.I.-C 
Cook, A.R 
Keywords: 2009 H1N1 influenza
adult
aged
antibody titer
Article
cohort analysis
controlled study
diagnostic accuracy
diagnostic test accuracy study
hemagglutination inhibition test
herd immunity
human
infection rate
influenza
Influenza virus
limit of detection
Markov chain
Monte Carlo method
nonhuman
predictive value
priority journal
sensitivity analysis
sensitivity and specificity
serology
Singapore
statistical model
threshold limit value
blood
genetics
immunology
Influenza A virus (H1N1)
Influenza, Human
isolation and purification
prospective study
virology
virus antibody
Antibodies, Viral
Hemagglutination Inhibition Tests
Humans
Influenza A Virus, H1N1 Subtype
Influenza, Human
Prospective Studies
Singapore
Issue Date: 2017
Citation: Zhao, X, Siegel, K, Chen, M.I.-C, Cook, A.R (2017). Rethinking thresholds for serological evidence of influenza virus infection. Influenza and other Respiratory Viruses 11 (3) : 202-210. ScholarBank@NUS Repository. https://doi.org/10.1111/irv.12452
Abstract: Introduction: For pathogens such as influenza that cause many subclinical cases, serologic data can be used to estimate attack rates and the severity of an epidemic in near real time. Current methods for analysing serologic data tend to rely on use of a simple threshold or comparison of titres between pre- and post-epidemic, which may not accurately reflect actual infection rates. Methods: We propose a method for quantifying infection rates using paired sera and bivariate probit models to evaluate the accuracy of thresholds currently used for influenza epidemics with low and high existing herd immunity levels, and a subsequent non-influenza period. Pre- and post-epidemic sera were taken from a cohort of adults in Singapore (n=838). Bivariate probit models with latent titre levels were fit to the joint distribution of haemagglutination-inhibition assay-determined antibody titres using Markov chain Monte Carlo simulation. Results: Estimated attack rates were 15% (95% credible interval: 12%-19%) for the first H1N1 pandemic wave. For a large outbreak due to a new strain, a threshold of 1:20 and a twofold rise (if pared sera is available) would result in a more accurate estimate of incidence. Conclusion: The approach presented here offers the basis for a reconsideration of methods used to assess diagnostic tests by both reconsidering the thresholds used and by analysing serological data with a novel statistical model. © 2017 The Authors. Influenza and Other Respiratory Viruses Published by John Wiley & Sons Ltd.
Source Title: Influenza and other Respiratory Viruses
URI: https://scholarbank.nus.edu.sg/handle/10635/173788
ISSN: 17502640
DOI: 10.1111/irv.12452
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