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

doi:10.1088/1674-1056/acd7d1

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.

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

Received: 06 March 2023
Revised: 23 April 2023
Accepted manuscript online: 23 May 2023

PACS:	89.20.-a	(Interdisciplinary applications of physics)
	89.70.-a	(Information and communication theory)
	89.75.-k	(Complex systems)

Fund: Project supported by the National Natural Science Foundation of China (Grant Nos. 62266030 and 61863025), International S & T Cooperation Projects of Gansu province (Grant No. 144WCGA166), and Longyuan Young Innovation Talents and the Doctoral Foundation of LUT.

Corresponding Authors: Fuzhong Nian
E-mail: gdnfz@lut.edu.cn

Cite this article:

Fuzhong Nian(年福忠), Xiaochen Yang(杨晓晨), and Yayong Shi(师亚勇) Analysis of radiation diffusion of COVID-19 driven by social attributes 2024 Chin. Phys. B 33 018904

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

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