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Author:

Li, Jianqiang (Li, Jianqiang.) | Wang, Jingnan (Wang, Jingnan.) | Xiong, Chengyao (Xiong, Chengyao.) | Wang, Yanan (Wang, Yanan.) | Pei, Yan (Pei, Yan.)

Indexed by:

EI Scopus

Abstract:

Corona Virus Disease 2019 (Covid-19) is a war between all humans and viruses. The outbreak of the Covid-19 epidemic has produced a large amount of data related to case information. Current related visualization studies are difficult to analyze these data, so a visualization analysis method for the Covid-19 epidemic situation in China is proposed. In this study, we present an effort to compile and analyze epidemiological outbreak information of Covid-19 based on the epidemic news and data in China after January 10, 2020. Through the analysis of data, it is concluded that the Covid-19 has the characteristics of a high infection rate and rapid transmission rate, and it also reflects the great contribution made by the Chinese government in controlling the epidemic. This study can obtain the hidden value behind the data, facilitate the understanding of the results of data analysis, and provide a reference for the government. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Keyword:

Data handling Epidemiology Data visualization Viruses Data mining Visualization

Author Community:

  • [ 1 ] [Li, Jianqiang]Faculty of Information, Beijing University of Technology, Beijing; 100124, China
  • [ 2 ] [Wang, Jingnan]Faculty of Information, Beijing University of Technology, Beijing; 100124, China
  • [ 3 ] [Xiong, Chengyao]Faculty of Information, Beijing University of Technology, Beijing; 100124, China
  • [ 4 ] [Wang, Yanan]Faculty of Information, Beijing University of Technology, Beijing; 100124, China
  • [ 5 ] [Pei, Yan]Computer Science Division, University of Aizu, Aizuwakamatsu; 965-8580, Japan

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ISSN: 1876-1100

Year: 2022

Volume: 791

Page: 43-51

Language: English

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 1

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 5

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