Literature DB >> 11315089

A hierarchical Bayesian model to predict the duration of immunity to Haemophilus influenzae type b.

K Auranen1, M Eichner, H Käyhty, A K Takala, E Arjas.   

Abstract

A hierarchical Bayesian regression model is fitted to longitudinal data on Haemophilus influenzae type b (Hib) serum antibodies. To estimate the decline rate of the antibody concentration, the model accommodates the possibility of unobserved subclinical infections with Hib bacteria that cause increasing concentrations during the study period. The computations rely on Markov chain Monte Carlo simulation of the joint posterior distribution of the model parameters. The model is used to predict the duration of immunity to subclinical Hib infection and to a serious invasive Hib disease.

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Year:  1999        PMID: 11315089     DOI: 10.1111/j.0006-341x.1999.01306.x

Source DB:  PubMed          Journal:  Biometrics        ISSN: 0006-341X            Impact factor:   2.571


  3 in total

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Authors:  Pejman Rohani; Aaron A King
Journal:  Trends Ecol Evol       Date:  2010-10       Impact factor: 17.712

2.  Dynamics of naturally acquired antibody against Haemophilus influenzae type a capsular polysaccharide in a Canadian Aboriginal population.

Authors:  Angjelina Konini; Eli Nix; Marina Ulanova; Seyed M Moghadas
Journal:  Prev Med Rep       Date:  2016-01-26

3.  A dynamic Bayesian Markov model for health economic evaluations of interventions in infectious disease.

Authors:  Katrin Haeussler; Ardo van den Hout; Gianluca Baio
Journal:  BMC Med Res Methodol       Date:  2018-08-02       Impact factor: 4.615

  3 in total

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