Mathematical Analysis of SIR Model for COVID-19 Transmission

Due to the recent threatening pandemic COVID-19, the research area of this disease is increasing. This paper tries to establish COVID-19 infection transmission by Susceptible-Infectious-Recovered (SIR) compartmental model for epidemic prediction and prevention. The model is built based on the secondary data of the infected persons and discharged patients. It is considered as a valuable tool in public health sector, as it can provide suggestions about the fatality of pandemic to take necessary actions for preventing the infections. COVID-19 is spreading worldwide extremely, and at present it becomes both local and global concern. This model can show the fatality of COVID-19 with time and can predict whether the disease will further spread or abolish completely. This study stresses on vaccination to reduce the infection of the disease. It can provide how many people are needed to be vaccinated to create herd immunity against COVID-19. Overtime the immunity due to vaccination may decrease and after a fixed period the immunity of COVID-19 due to vaccination may extinct completely. The article attempts to give a mathematical presentation to aware the immunity loss individuals with other susceptible. It also tries to alert the people about the re-infection of the previous COVID-19 infected persons. The aim of this study is to minimize both global economic losses and deaths due to COVID-19.