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

In this paper, we propose a new model to describe the blood type distribution of new Coronavirus (COVID-19) cases using the Bayesian Poisson - Hidden Markov Model (BP-HMM). With the help of the GIBBS sampler; We first identify the number of hidden states fitting European (EU) and African (AF) data sets of COVID-19 cases by blood type frequencies. The study then compares the state-dependent mean of infection within and across the two geographical areas. The study findings show that the number of hidden states and rate of infection within and across the two geographical areas differ according to blood type.