Forecasting of COVID-19 Trends in Bangladesh Using Machine Learning Approaches

Abstract

Bangladesh, a low-to-middle income economy country with one of the world’s densest populations, is ranked 26th worldwide having a positive case rate of 25%-30% of COVID-19 confirmed instances as of July 28, 2021. The recent researches related to COVID-19 focus on addressing mental health problems caused by it, and fewer works have been performed to forecast its trends using machine learning (ML), especially in Bangladesh. Therefore, this research attempts to predict the infected, death, and recovery cases for COVID-19 in Bangladesh using four ML techniques FB Prophet, ARIMA, SARIMAX, LSTM and com pare their forecasting performance to find out the best prediction model. The experimental results showed that for ‘Detected’ and ‘Death’ case, LSTM and SARIMAX performed better than other models with (RMSE = 1836.79, MAE = 1056.36) and (RMSE = 24.70, MAE = 15.54), respectively. In the ‘Recovery’ case, the best result was found in the ARIMA model with RMSE = 558.87, MAE = 299.64. According to the analysis, this research work can help predict the trends of COVID-19 cases in the future and help policymakers taking necessary precautions to control the detection and death rate in the country.