Transmission Mechanism of Post-COVID-19 Emergency Supply Chain Based on Complex Network: An Improved SIR Model

Abstract

Since the COVID-19 epidemic swept the world, the emergency supply chain (ESC) has faced serious uncertainty risks. To maintain the stability of the emergency supply, risk prevention and contingency measures must be prepared. In this paper, the authors first obtain the initial risk value of 0.4 using the fuzzy comprehensive evaluation approach and then build an improved SIR model based on a complex network to investigate the risk propagation law of the ESC. The simulation results show that (1) the high number of nodes becomes the initial risk source, the risk propagates faster and the peak value arrives two days earlier on average; (2) the initial infection rate gradually increases from 0.2 to 0.4, 0.6, and 0.8, and the risk spread speed also accelerates; (3) the recovery rate of network nodes increases gradually from 0.1 to 0.2, 0.3, and 0.4, and the influence range of risk propagation decreases inversely; (4) appropriately increasing the deletion rate of network nodes is conducive to improving the stability of the ESC network. Given the above ESC risk propagation law, this paper proposes relevant risk prevention measures and suggests that a risk early warning system of node enterprises should be established in combination with the target immunization strategy. For ESC risk management, the result has significant theoretical and practical implications.

Epidemic Waves and Exact Solutions of a Sequence of Nonlinear Differential Equations Connected to the SIR Model of Epidemics

“…Epidemic models can also be applied for the description of other processes, such as the spread of ideas (for overviews, see [ 3 , 63 ]). We also note the use of epidemic models for the study of COVID-19 spreading [ 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 , 78 ], as well as the numerical methods for obtaining solutions to such models [ 79 , 80 ].…”