A Topological Data Analysis Approach to the COVID-19

Zhichao Lu; Heng Liu

doi:10.1109/ITAIC54216.2022.9836495

A Topological Data Analysis Approach to the COVID-19

Zhichao Lu, Heng Liu

School of Information and Electronics

Beijing Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

Topological data analysis (TDA) has emerged as a method for understanding data clouds by extracting and comparing the structure of datasets. This paper applies one of the TDA instruments available which is called the Mapper algorithm to analyze the COVID-19 data in China. The Mapper graphs generated by the algorithm successfully reflect the development of COVID-19 across China and provide a relatively complete visualization of the pandemic. Experimental results indicate that the proposed method may have the potential to become a robust predictive tool for the spread of the coronavirus.

Original language	English
Title of host publication	IEEE 10th Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2022
Editors	Bing Xu
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	469-473
Number of pages	5
ISBN (Electronic)	9781665422079
DOIs	https://doi.org/10.1109/ITAIC54216.2022.9836495
Publication status	Published - 2022
Event	10th IEEE Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2022 - Chongqing, China Duration: 17 Jun 2022 → 19 Jun 2022

Publication series

Name	IEEE Joint International Information Technology and Artificial Intelligence Conference (ITAIC)
Volume	2022-June
ISSN (Print)	2693-2865

Conference

Conference	10th IEEE Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2022
Country/Territory	China
City	Chongqing
Period	17/06/22 → 19/06/22

Keywords

COVID-19
Mapper
Topological Data Analysis
Visualization

Access to Document

10.1109/ITAIC54216.2022.9836495

Cite this

Lu, Z., & Liu, H. (2022). A Topological Data Analysis Approach to the COVID-19. In B. Xu (Ed.), IEEE 10th Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2022 (pp. 469-473). (IEEE Joint International Information Technology and Artificial Intelligence Conference (ITAIC); Vol. 2022-June). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ITAIC54216.2022.9836495

Lu, Zhichao ; Liu, Heng. / A Topological Data Analysis Approach to the COVID-19. IEEE 10th Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2022. editor / Bing Xu. Institute of Electrical and Electronics Engineers Inc., 2022. pp. 469-473 (IEEE Joint International Information Technology and Artificial Intelligence Conference (ITAIC)).

@inproceedings{93d852d007fc447da8c5f05945fbcbb1,

title = "A Topological Data Analysis Approach to the COVID-19",

abstract = "Topological data analysis (TDA) has emerged as a method for understanding data clouds by extracting and comparing the structure of datasets. This paper applies one of the TDA instruments available which is called the Mapper algorithm to analyze the COVID-19 data in China. The Mapper graphs generated by the algorithm successfully reflect the development of COVID-19 across China and provide a relatively complete visualization of the pandemic. Experimental results indicate that the proposed method may have the potential to become a robust predictive tool for the spread of the coronavirus.",

keywords = "COVID-19, Mapper, Topological Data Analysis, Visualization",

author = "Zhichao Lu and Heng Liu",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 10th IEEE Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2022 ; Conference date: 17-06-2022 Through 19-06-2022",

year = "2022",

doi = "10.1109/ITAIC54216.2022.9836495",

language = "English",

series = "IEEE Joint International Information Technology and Artificial Intelligence Conference (ITAIC)",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "469--473",

editor = "Bing Xu",

booktitle = "IEEE 10th Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2022",

address = "United States",

}

Lu, Z & Liu, H 2022, A Topological Data Analysis Approach to the COVID-19. in B Xu (ed.), IEEE 10th Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2022. IEEE Joint International Information Technology and Artificial Intelligence Conference (ITAIC), vol. 2022-June, Institute of Electrical and Electronics Engineers Inc., pp. 469-473, 10th IEEE Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2022, Chongqing, China, 17/06/22. https://doi.org/10.1109/ITAIC54216.2022.9836495

A Topological Data Analysis Approach to the COVID-19. / Lu, Zhichao; Liu, Heng.
IEEE 10th Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2022. ed. / Bing Xu. Institute of Electrical and Electronics Engineers Inc., 2022. p. 469-473 (IEEE Joint International Information Technology and Artificial Intelligence Conference (ITAIC); Vol. 2022-June).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - A Topological Data Analysis Approach to the COVID-19

AU - Lu, Zhichao

AU - Liu, Heng

PY - 2022

Y1 - 2022

N2 - Topological data analysis (TDA) has emerged as a method for understanding data clouds by extracting and comparing the structure of datasets. This paper applies one of the TDA instruments available which is called the Mapper algorithm to analyze the COVID-19 data in China. The Mapper graphs generated by the algorithm successfully reflect the development of COVID-19 across China and provide a relatively complete visualization of the pandemic. Experimental results indicate that the proposed method may have the potential to become a robust predictive tool for the spread of the coronavirus.

AB - Topological data analysis (TDA) has emerged as a method for understanding data clouds by extracting and comparing the structure of datasets. This paper applies one of the TDA instruments available which is called the Mapper algorithm to analyze the COVID-19 data in China. The Mapper graphs generated by the algorithm successfully reflect the development of COVID-19 across China and provide a relatively complete visualization of the pandemic. Experimental results indicate that the proposed method may have the potential to become a robust predictive tool for the spread of the coronavirus.

KW - COVID-19

KW - Mapper

KW - Topological Data Analysis

KW - Visualization

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U2 - 10.1109/ITAIC54216.2022.9836495

DO - 10.1109/ITAIC54216.2022.9836495

M3 - Conference contribution

AN - SCOPUS:85136343698

T3 - IEEE Joint International Information Technology and Artificial Intelligence Conference (ITAIC)

SP - 469

EP - 473

BT - IEEE 10th Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2022

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PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 10th IEEE Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2022

Y2 - 17 June 2022 through 19 June 2022

ER -

Lu Z, Liu H. A Topological Data Analysis Approach to the COVID-19. In Xu B, editor, IEEE 10th Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2022. Institute of Electrical and Electronics Engineers Inc. 2022. p. 469-473. (IEEE Joint International Information Technology and Artificial Intelligence Conference (ITAIC)). doi: 10.1109/ITAIC54216.2022.9836495

A Topological Data Analysis Approach to the COVID-19

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