Issue |
EPL
Volume 148, Number 1, October 2024
|
|
---|---|---|
Article Number | 11001 | |
Number of page(s) | 7 | |
Section | Statistical physics and networks | |
DOI | https://doi.org/10.1209/0295-5075/ad7a9e | |
Published online | 04 October 2024 |
Modeling and analysis of COVID-19 spreading based on complex network theory
1 School of Physics and Electronic Science, East China Normal University - Shanghai, 200241, China
2 School of computer and Software, Southwest Petroleum University - Chengdu, 610500, China
3 Shanghai Key Laboratory of Multidimensional Information Processing, East China Normal University Shanghai, 200241, China
Received: 6 August 2024
Accepted: 13 September 2024
Complex networks can effectively describe interactions within real-world complex systems. In researches of epidemic spreading, scientists constructed various physical contact networks between individuals on the microscopic scale and the metapopulation networks on the macroscopic scale. These different types of network structures significantly impact the propagation dynamics of epidemic in human society. For instance, population flows in global airline networks influence the speed and arrival time of epidemics across large-scale space. In this paper we review the epidemic spreading models on various network structures, including fully mixed networks, three types of lower-order networks, three types of higher-order networks, metapopulation networks, and multiple strains competitive epidemic spreading models. We also provide an overview of the application of complex network theory in the COVID-19 pandemic, covering topics of prediction, prevention, and control of the epidemic. Finally, we discuss the strengths and limitations of these models and propose perspectives for future research.
© 2024 EPLA
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