Effective Supply Chain Management Using SEIR Simulation Models for Efficient Decision-Making During COVID-19

The coronavirus illness epidemic of 2019 (COVID-19), the most devastating to world health, has affected not only demand but also supply. It has evolved into an economic shock that has had a significant impact on our daily lives and worldview. The economic fallout has posed significant challenges regarding raw materials and final product flow, thereby affecting manufacturing. In this paper, a simulation model of the susceptible-exposed-infectious-recovered (SEIR) network is built, which forecasts how infected and healed people will act. The graphs for each parameter are generated from the SEIR model output behavior, and the model is then used to identify the behavior of patients who are vulnerable, exposed, infected, and recovered. Analyzing the graph makes it simple to comprehend the behavior and prepare backup facilities, helping to reduce patient fatalities. With the help of the SEIR simulation model and its output behavior, an attempt has been made to establish a perfect supply chain mechanism in a different pandemic situation. These models can also be applied to predict the peak stage of any pandemic and improve the existing supply chain.