Accepted for/Published in: JMIR Public Health and Surveillance
Date Submitted: Sep 13, 2020
Date Accepted: Oct 25, 2020
Date Submitted to PubMed: Oct 27, 2020
A Network Analysis of COVID-19 Epidemic in Mainland China by K-Core Decomposition
ABSTRACT
Background:
Since the outbreak of coronavirus disease (COVID-19) in December 2019 in Wuhan, Hubei Province, China, the frequent interregional contacts and high rate of infection spread catalyzed the formation of its epidemic network.
Objective:
The aim of this study was to identify influential nodes and highlight the hidden structural properties of COVID-19 epidemic network, which we believe it is central for epidemic prevention and control.
Methods:
We first construct COVID-19 epidemic network among provinces in mainland China, after revealing some basic characteristics by the degree distribution, the k-core decomposition method is employed to provide some static and dynamic evidence of figuring out the influential nodes and hierarchical structure, and then we exhibit the influence power of the above nodes and its evolution.
Results:
Only a small fraction tend to have relatively strong outward or inward epidemic transmission effects. Three provinces of Hubei, Beijing and Guangzhou rank in the first top three of out-degree, and the in-degree top three relates to provinces of Beijing, Henan and Liaoning. In terms of hierarchical structure of COVID-19 epidemic network over the whole period, more than half of 31 provinces are in the innermost core. Considering the correlation of the characteristics and coreness of each province, we identify some significant negative and positive factors. Specific to the dynamic transmission process of COVID-19 epidemic, three provinces of Anhui, Beijing and Guangdong always show the highest coreness from the third to sixth week, and Hubei province maintained the highest until the fifth week, and suddenly dropped to the lowest in the sixth week. We also find that the out-strength of the innermost nodes is larger than their in-strength before January 27, 2020, while then there is a reversal.
Conclusions:
Such a better understanding of how epidemic network form and function may help reduce the damaging effects of COVID-19 to China as well as other countries and territories worldwide.
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