Bayesian Hidden Markov Modeling of Blood Type Distribution for COVID-19 Cases Using Poisson Distribution

    December 2023 in “ International journal of statistics and probability ”
    Johnson Joseph Kwabina Arhinful, Okyere Gabriel Asare, Adebanji Atinuke Olusola, Oliver Johnson, Burnett Tetteh Accam
    Image
    Studysummary In this study, the authors used a Bayesian Poisson - Hidden Markov Model to analyze COVID-19 cases by blood type in Europe and Africa, finding differences in hidden states and infection rates based on blood type across these regions. Our plain-language summary of this paper — not a Tressless recommendation.
    This study uses a Bayesian Poisson - Hidden Markov Model (BP-HMM) to analyze the distribution of blood types among COVID-19 cases in European (EU) and African (AF) populations. By employing the Gibbs sampler algorithm with OpenBugs, the researchers identified the number of hidden states that best fit the data sets. The findings reveal that the number of hidden states and the infection rates vary by blood type within and between the two regions.
    Discuss this study in the Community →