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Proceedings of the 4th International Conference on Public Management and Intelligent Society, PMIS 2024, 15–17 March 2024, Changsha, China

Research Article

Infectious Disease Risk Transmission Mechanism in Cold Chain Transportation Link and Simulation Study

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  • @INPROCEEDINGS{10.4108/eai.15-3-2024.2346574,
        author={Ruoxin  Yang and Jiahuan  Li},
        title={Infectious Disease Risk Transmission Mechanism in Cold Chain Transportation Link and Simulation Study},
        proceedings={Proceedings of the 4th International Conference on Public Management and Intelligent Society, PMIS 2024, 15--17 March 2024, Changsha, China},
        publisher={EAI},
        proceedings_a={PMIS},
        year={2024},
        month={6},
        keywords={cold chain transportation; infectious disease prevention; infectious disease risk transmission; sir infectious disease modeling},
        doi={10.4108/eai.15-3-2024.2346574}
    }
    
  • Ruoxin Yang
    Jiahuan Li
    Year: 2024
    Infectious Disease Risk Transmission Mechanism in Cold Chain Transportation Link and Simulation Study
    PMIS
    EAI
    DOI: 10.4108/eai.15-3-2024.2346574
Ruoxin Yang1,*, Jiahuan Li1
  • 1: Xi 'an Science and Technology University
*Contact email: healer221@163.com

Abstract

In order to study the infectious disease risk propagation process and propagation mechanism in the cold chain transportation link, this paper, based on the accident causation theory, obtains the infectious disease risk propagation mechanism in the cold chain transportation process by constructing the cold chain transportation infectious disease propagation risk intensity system and the cold chain transportation infectious disease immunity evaluation index system; and applies the SIR viral propagation model to compute two parameter values of risk propagation of the Cold Chain Transport Company A as a case study, to Simulate the spreading process of infectious disease risk in the cold chain transportation network with Cold Chain Transportation Company A as the core, in addition, analyze the influence of each parameter of the risk spreading model on the spreading process by adjusting the values of each parameter.

Keywords
cold chain transportation; infectious disease prevention; infectious disease risk transmission; sir infectious disease modeling
Published
2024-06-07
Publisher
EAI
http://dx.doi.org/10.4108/eai.15-3-2024.2346574
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