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Spreading Dynamics Analysis for Railway Networks
2nd International Conference on Neural Computing for Advanced Applications, NCAA 2021 ; 1449:154-165, 2021.
Article in English | Scopus | ID: covidwho-1437240
ABSTRACT
The 2019 Coronavirus Disease (COVID-19), with the characteristics of rapid onset, strong infectivity, fast transmission and wide susceptibility, has quickly swept China since its appearance in Wuhan, Hubei province. COVID-19 spreads among people mainly by movement and close contact. Railway plays an important role in transport people national-wide as its essential role in public transportation, which conduced to the spreading of COVID-19 from Hubei province to other provinces in some sense. Inspired by this, this paper collected the data of Trains with Infectors (TwI) reported by the national health commission of the People’s Republic of China. Then the spreading of COVID-19 via railway network with the concept of complex network is analyzed. Results show that nodes with higher centrality tends to provide more TwI, and the closure of Wuhan railway station significantly prevents the spreading of COVID-19. © 2021, Springer Nature Singapore Pte Ltd.

Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 2nd International Conference on Neural Computing for Advanced Applications, NCAA 2021 Year: 2021 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 2nd International Conference on Neural Computing for Advanced Applications, NCAA 2021 Year: 2021 Document Type: Article