Time based Meticulous analysis of pandemic spreading ratio using Simpy framework

Abstract

Due to the unavoidable spread of COVID-19 and even taking all substantial measures, the ratio of infected people and death rate seems to be out of control. In this increasingly worsening situation, the aim of this article is that it is important to take extraordinary measures to deal with this exceptional pandemic situation, and this is only possible if the actual ratio of the spread of the pandemic is known. Therefore, ingenious pandemic models are being developed to produce real-time infection statistics on an hourly, weekly, and monthly basis. This clever model leverages well-known data sets and when they will be applied to determine the status of three types of infections: the number of infected people, the time the pandemic started, and the time it ended. The time-based results are generated by conduction simulation in the Simpy Python framework, and the resulting results are characteristic of the real-time infection spread ratio. This shows when extraordinary measures for the infection ratio are necessary and when they become reasonable.