中国物理B(英文版)2024,Vol.33Issue(1) :861-868.DOI:10.1088/1674-1056/acd7d1

Analysis of radiation diffusion of COVID-19 driven by social attributes

年福忠 杨晓晨 师亚勇
中国物理B(英文版)2024,Vol.33Issue(1) :861-868.DOI:10.1088/1674-1056/acd7d1

Analysis of radiation diffusion of COVID-19 driven by social attributes

年福忠 1杨晓晨 1师亚勇2
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作者信息

  • 1. Lanzhou University of Technology,School of Computer & Communication,Lanzhou 730050,China
  • 2. University of Science and Technology Beijing,School of Computer & Communication Engineering,Beijing 100083,China
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Abstract

This paper first estimated the infectious capacity of COVID-19 based on the time series evolution data of confirmed cases in multiple countries.Then,a method to infer the cross-regional spread speed of COVID-19 was introduced in this paper,which took the gross domestic product(GDP)of each region as one of the factors that affect the spread speed of COVID-19 and studied the relationship between the GDP and the infection density of each region(mainland China,the United States,and EU countries).In addition,the geographic distance between regions was also considered in this method and the effect of geographic distance on the spread speed of COVID-19 was studied.Studies have shown that the probability of mutual infection of these two regions decreases with increasing geographic distance.Therefore,this paper proposed an epidemic disease spread index based on GDP and geographic distance to quantify the spread speed of COVID-19 in a region.The analysis results showed a strong correlation between the epidemic disease spread index in a region and the number of confirmed cases.This finding provides reasonable suggestions for the control of epidemics.Strengthening the control measures in regions with higher epidemic disease spread index can effectively control the spread of epidemics.

Key words

COVID-19 basic reproduction number/gross domestic product(GDP)/geographic distance/cross-regional spread

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基金项目

National Natural Science Foundation of China(62266030)

National Natural Science Foundation of China(61863025)

International S & T Cooperation Projects of Gansu province(144WCGA166)

Longyuan Young Innovation Talents and the Doctoral Foundation of LUT()

出版年

2024
中国物理B(英文版)
中国物理学会和中国科学院物理研究所

中国物理B(英文版)

CSTPCDEI
影响因子:0.995
ISSN:1674-1056
参考文献量60
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