The Bayesian Hidden Markov Chain Modeling of the Ghana COVID-19 Blood Type Infection Distribution
DOI:
https://doi.org/10.23755/rm.v54i0.1602Keywords:
\textbf{Keywords}, Hidden Markov Chain, Bayesian-Poisson Hidden Markov, COVID-19, Transition ProbabilitiesAbstract
This work uses the Bayesian Poisson-Hidden Markov Model (BP-HMM) to develop a model that properly describes the blood type distribution among newly diagnosed COVID-19 patients. The study estimated the number of Hidden states for COVID-19 datasets from Ghana based on blood type distribution. The study's results show that the number of hidden states and rates of infection vary by blood type, four hidden states were found for the $AB^{-}$ blood group whereas all the others had five each. It was established that, the blood group O had the highest infection rate and more susceptible for an infected person deteriorated through the transition states.
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