Spectrum Analysis of Contact Network for Public Policy in a Pandemic

被引:0
|
作者
Xu, Qi [1 ]
机构
[1] Univ Elect Sci & Technol China, Sch Math Sci, Chengdu 611731, Peoples R China
关键词
Mathematical models; Biological system modeling; Public policy; Infectious diseases; Eigenvalues and eigenfunctions; Computational modeling; Analytical models; Contact network; infectious disease; laplacian matrix; public policy; spectrum analysis; transmission network;
D O I
10.1109/ACCESS.2022.3177193
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In a pandemic, in order to slow down the spread of the virus, protect national health, and maintain the normal operation of economic activities, countries around the world will formulate public policies to limit the number of citizens that can gather. Our research focuses on how to achieve optimal public policy under different conditions. Traditional SIR and SEIR models can well reflect the transmission process and obtain credible prediction results from a macro perspective, but lack the sensitivity of micro data, and cannot assess the risk of epidemic transmission brought by close contacts and sub-close contacts. Based on the Barabasi-Albert scale-free network and the Random spanning tree algorithm, we generate a simulated spread network for non-specific infectious diseases. At the same time, we also generate group networks under different gather constraints. The superposition of the two forms a composite contact network. Our research work on the contact network shows that after considering close contacts and sub-close contacts, the public policy optimization problem of slowing the spread of the epidemic can be answered by the spectrum analysis of the contact network. We perform computer simulations and theoretical proofs of this model, and conduct a transmission analysis of its process.
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页码:55574 / 55582
页数:9
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