Analyzing the Application of SIR Model to Study the Outbreak of COVID-19: A Case Study in Pakistan

Abstract

The current study aims to examine the exponential rate of the spread of COVID-19 by employing a system dynamic model. The outbreak of COVID-19 was first evidenced on Feb 26, 2020 in Pakistan. The local bodies and law enforcing agencies took the initial preventive measures to restrict COVID-19 to a particular locality but all in vain. A large number of people were infected by this virus which increased the death rate countrywide. The numbers of infected people were alarming and a need was felt to develop the model to calculate the existing reproduction number and transmission rate and highlight its varied values in the coming days. People-friendly measures and government-based policies must be explored to fight against this deadly disease. This paper aims to develop an epidemic model using the system dynamic framework of simulation software STELLA. Additionally, the current study’s purpose is to experiment with the system dynamic model to replicate the progression of the communicable disease and probe multiple combinations of people-based and government-based measures to reduce the spread of the COVID-19 pandemic. These containment measures are of two types; people-based measures and government-based measures which directly affect the reproduction number and infection growth rate of the mitigating circumstances due to COVID-19. Combined efforts of the public and government can combat this global pandemic. The reduced number of reproduction number/recurring cases and infection growth rate are the key metrics to judge and evaluate the effectiveness of containment/ control measures. Therefore, this research points to a more holistic combination of public and government-oriented measures that play a vital role in reducing the increasing infection rate of COVID-19. Simulation results were traced to replicate the real-life settings against four combinations of containmentmeasures in tabular form and graphical form.