Exploration and prediction of COVID-19 pandemic in Bangladesh using numerical approach - Rezaul Karim; M. Ali Akbar; Saikh Shahjahan Miah; M. A. Bkar Pk; Pinakee Dey; M. S. Osman (Discover Data)
Abstract The COVID-19 pandemic has had an impact on people's health, lifestyles, and economies all over the world. The coronavirus model with a time delay effect is analyzed mathematically; however, a developing country like Bangladesh, which is a densely populated country compared to other countries in the world, has been affected the most. This paper’s major goal is to study and quantitatively model the dynamics of coronavirus transmission. To predict the spread of infections, we frequently employ the coronavirus's fundamental SIR model. Due to the limitations of the solution of a specific equation, we introduce the Euler, Modified Euler, and RK methods (EMERK) to partially solve the three fundamental equations of the SIR model. In this paper, we study the performance and comparison of these three methods in solving the model. We also discuss their performance using actual data and numerical experiments, showing that there is a good argument and accurate solutions for solving this type of problem. At last, the suggested model's viability and the efficacy of the control schemes were demonstrated through the presentation of analysis and numerical simulation. The outcome of this study concludes that outbreaks should be controlled, which ensures social and economic stability, as shown in the figure.