COVID-19 Confirmed Cases and Deaths Prediction in Bangladesh Using Hidden Markov Model

Abstract

The number of people affected by Coronavirus is quite concerning in Bangladesh. It has become a necessity to forecast the future cases since it involves ensuring adequate resources to help people and imposing strict guidelines to deal with this epidemic. This research is about predicting upcoming COVID-19 confirmed cases and deaths from a time series dataset using Hidden Markov Model. The optimal number of hidden states were determined using AIC and BIC. The proposed models are implemented to forecast the daily confirmed cases and daily deaths of Bangladesh for next 90 days.