Scenario-Based Analysis about COVID-19 Outbreak in Iran using Systematic Dynamics Modeling - with a Focus on the Transportation System

Document Type : Original Article

Authors

1 M.Sc., Grad., Department of Industrial Engineering and Management Systems, Amirkabir University of Technology, Tehran, Iran.

2 Department of Industrial Engineering and Management Systems, Amirkabir University of Technology, Tehran, Iran.

3 Assistant Professor, Department of Industrial Engineering and Management Systems, Amirkabir University of Technology, Tehran, Iran.

Abstract

Today, coronavirus (COVID-19) has become a major global threat. A lot of programs are proposed to prevent and estimate its associated processes due to the high risk of its transmitting among humans and the lack of drugs and vaccines to stop it. COVID-19 was first reported on 31 December 2019 in Wuhan, China. After a short time, the disease spread to other countries and became a global disease. According to the lives of most people, the transportation system has a significant impact on controlling or spreading the disease. Therefore, this subsystem is considered as an element of a proposed system dynamics model in this article. This model examines two different scenarios for infected people, mortality rates, and recovery rates. The system is designed according to various subsystems such as health care systems, transportation, public contact, and the capacity of food and drug networks. In the proposed model of this paper, a flow structure is utilized to show the effects of different sections of systems and subsystems depend on the COVID-19 outbreak over a long time. The results of the proposed model show that different parts of the main system and its related subsystems have different sensitivities and effects. Analyzing this model will be useful for government decision-making based on the results of the two scenarios examined. It is assumed that there is no effective vaccine or drug in the next 6 months. The results of the proposed model show that different changes in subsystems could increase COVID-19 mortality in six months from 10,500 to more than 1.6 million. Therefore, the mortality rate of this disease depends on the policies and behaviors of the factors influencing the model. Consequently, the mortality rate can be reduced based on proper planning against each scenario.

Keywords

References

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