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
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
A network analysis of 2019-nCoV epidemic in mainland China by k-core decomposition
ABSTRACT
Frequent interregional contacts and the high rate of infection spread catalyzed the formation of 2019-nCoV epidemic network. Identifying influential nodes and highlighting the hidden structural properties of the network is central for epidemic prevention and control. In this paper, we first construct the 2019-nCoV epidemic network among provinces in mainland China, after using the degree distribution to reveal some basic characteristics, 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 yield unexpected information on which are influential nodes and how important they are, as well as their geographic distribution and dynamic modes. Such a better understanding of how epidemic network form and function may help reduce the damaging effects of 2019-nCoV.
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