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R Soc Open Sci. 2018 Jul 25;5(7):180113. doi: 10.1098/rsos.180113. eCollection 2018 Jul.
Bayesian inference of antigenic and non-antigenic variables from haemagglutination inhibition assays for influenza surveillance.
Adabor ES1,2, Ndifon W2,3.
Author information
Abstract
Haemagglutination inhibition (HI) assays are typically used for comparing and characterizing influenza viruses. Data obtained from the assays (titres) are used quantitatively to determine antigenic differences between influenza strains. However, the use of these titres has been criticized as they sometimes fail to capture accurate antigenic differences between strains. Our previous analytical work revealed how antigenic and non-antigenic variables contribute to the titres. Building on this previous work, we have developed a Bayesian method for decoupling antigenic and non-antigenic contributions to the titres in this paper. We apply this method to a compendium of HI titres of influenza A (H3N2) viruses curated from 1968 to 2016. Remarkably, the results of this fit indicate that the non-antigenic variable, which is inversely correlated with viral avidity for the red blood cells used in HI assays, oscillates during the course of influenza virus evolution, with a period that corresponds roughly to the timescale on which antigenic variants replace each other. Together, the results suggest that the new Bayesian method is applicable to the analysis of long-term dynamics of both antigenic and non-antigenic properties of influenza virus.
KEYWORDS:
Bayesian inference; haemagglutination inhibitions assays; influenza surveillance; influenza virus
PMID: 30109067 PMCID: PMC6083687 DOI: 10.1098/rsos.180113
Free PMC Article
Bayesian inference of antigenic and non-antigenic variables from haemagglutination inhibition assays for influenza surveillance.
Adabor ES1,2, Ndifon W2,3.
Author information
Abstract
Haemagglutination inhibition (HI) assays are typically used for comparing and characterizing influenza viruses. Data obtained from the assays (titres) are used quantitatively to determine antigenic differences between influenza strains. However, the use of these titres has been criticized as they sometimes fail to capture accurate antigenic differences between strains. Our previous analytical work revealed how antigenic and non-antigenic variables contribute to the titres. Building on this previous work, we have developed a Bayesian method for decoupling antigenic and non-antigenic contributions to the titres in this paper. We apply this method to a compendium of HI titres of influenza A (H3N2) viruses curated from 1968 to 2016. Remarkably, the results of this fit indicate that the non-antigenic variable, which is inversely correlated with viral avidity for the red blood cells used in HI assays, oscillates during the course of influenza virus evolution, with a period that corresponds roughly to the timescale on which antigenic variants replace each other. Together, the results suggest that the new Bayesian method is applicable to the analysis of long-term dynamics of both antigenic and non-antigenic properties of influenza virus.
KEYWORDS:
Bayesian inference; haemagglutination inhibitions assays; influenza surveillance; influenza virus
PMID: 30109067 PMCID: PMC6083687 DOI: 10.1098/rsos.180113
Free PMC Article