An initial visual analysis of the relationship between COVID-19 and local community features

Jie Hua; Mao Lin Huang; Chenglin Zhao; Shuyang Hua; Catherine Shih

doi:10.1109/iv51561.2020.00125

An initial visual analysis of the relationship between COVID-19 and local community features

Jie Hua, Mao Lin Huang, Chenglin Zhao, Shuyang Hua, Catherine Shih

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

6 Citations (Scopus)

Abstract

Virus outbreaks are threats to humanity, and coronaviruses are the latest of many epidemics in the last few decades. In this work, we conduct a non-medical/clinical approach, generating graphs from five features concluded from the COVID-19 outbreak data and local community data in NSW (New South Wales), Australia, and offering insights from a visual analysis perspective The results show that household income, population density and ethnicity affect the infection in different areas. Features such as human behaviours need to be imported for further COVID-19 research in the data science sector. This work is an initial step into this area and allows more insights to be brought into future COVID-19 research through a visual analysis perfective.

Original language	English
Title of host publication	2020 24th International Conference Information Visualisation (IV)
Editors	Ebad Banissi, Farzad Khosrow-Shahi, Anna Ursyn, Mark W. McK. Bannatyne, João Moura Pires, Nuno Datia, Kawa Nazemi, Boris Kovalerchuk, John Counsell, Andrew Agapiou, Zora Vrcelj, Hing-Wah Chau, Mengbi Li, Gehan Nagy, Richard Laing, Rita Francese, Muhammad Sarfraz, Fatma Bouali, Gilles Venturin, Marjan Trutschl, Urska Cvek, Heimo Müller, Minoru Nakayama, Marco Temperini, Tania Di Mascio, Filippo Sciarrone, Veronica Rossano, Ralf Dörner, Loredana Caruccio, Autilia Vitiello, Weidong Huang, Michele Risi, Ugo Erra, Razvan Andonie, Muhammad Aurangzeb Ahmad, Ana Figueiras, Alfredo Cuzzocrea, Mabule Samuel Mabakane
Place of Publication	Piscataway, NJ
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	718-722
Number of pages	5
ISBN (Electronic)	9781728191348
ISBN (Print)	9781728191355
DOIs	https://doi.org/10.1109/iv51561.2020.00125
Publication status	Published - 2020
Externally published	Yes
Event	24th International Conference Information Visualisation, IV 2020 - Melbourne, Australia Duration: 7 Sept 2020 → 11 Sept 2020

Publication series

Name
ISSN (Print)	1550-6037
ISSN (Electronic)	2375-0138

Conference

Conference	24th International Conference Information Visualisation, IV 2020
Country/Territory	Australia
City	Melbourne
Period	7/09/20 → 11/09/20

Keywords

visual analysis
graph visualisation
graph drawing
coronavirus
COVID-19

Access to Document

10.1109/iv51561.2020.00125Licence: Unspecified

Cite this

Hua, J., Lin Huang, M., Zhao, C., Hua, S., & Shih, C. (2020). An initial visual analysis of the relationship between COVID-19 and local community features. In E. Banissi, F. Khosrow-Shahi, A. Ursyn, M. W. McK. Bannatyne, J. M. Pires, N. Datia, K. Nazemi, B. Kovalerchuk, J. Counsell, A. Agapiou, Z. Vrcelj, H.-W. Chau, M. Li, G. Nagy, R. Laing, R. Francese, M. Sarfraz, F. Bouali, G. Venturin, M. Trutschl, U. Cvek, H. Müller, M. Nakayama, M. Temperini, T. Di Mascio, F. Sciarrone, V. Rossano, R. Dörner, L. Caruccio, A. Vitiello, W. Huang, M. Risi, U. Erra, R. Andonie, M. A. Ahmad, A. Figueiras, A. Cuzzocrea, ... M. S. Mabakane (Eds.), 2020 24th International Conference Information Visualisation (IV) (pp. 718-722). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/iv51561.2020.00125

Hua, Jie ; Lin Huang, Mao ; Zhao, Chenglin et al. / An initial visual analysis of the relationship between COVID-19 and local community features. 2020 24th International Conference Information Visualisation (IV). editor / Ebad Banissi ; Farzad Khosrow-Shahi ; Anna Ursyn ; Mark W. McK. Bannatyne ; João Moura Pires ; Nuno Datia ; Kawa Nazemi ; Boris Kovalerchuk ; John Counsell ; Andrew Agapiou ; Zora Vrcelj ; Hing-Wah Chau ; Mengbi Li ; Gehan Nagy ; Richard Laing ; Rita Francese ; Muhammad Sarfraz ; Fatma Bouali ; Gilles Venturin ; Marjan Trutschl ; Urska Cvek ; Heimo Müller ; Minoru Nakayama ; Marco Temperini ; Tania Di Mascio ; Filippo Sciarrone ; Veronica Rossano ; Ralf Dörner ; Loredana Caruccio ; Autilia Vitiello ; Weidong Huang ; Michele Risi ; Ugo Erra ; Razvan Andonie ; Muhammad Aurangzeb Ahmad ; Ana Figueiras ; Alfredo Cuzzocrea ; Mabule Samuel Mabakane. Piscataway, NJ : Institute of Electrical and Electronics Engineers (IEEE), 2020. pp. 718-722

@inproceedings{9c4c04894b9a4813aa753a22cad40bc7,

title = "An initial visual analysis of the relationship between COVID-19 and local community features",

abstract = "Virus outbreaks are threats to humanity, and coronaviruses are the latest of many epidemics in the last few decades. In this work, we conduct a non-medical/clinical approach, generating graphs from five features concluded from the COVID-19 outbreak data and local community data in NSW (New South Wales), Australia, and offering insights from a visual analysis perspective The results show that household income, population density and ethnicity affect the infection in different areas. Features such as human behaviours need to be imported for further COVID-19 research in the data science sector. This work is an initial step into this area and allows more insights to be brought into future COVID-19 research through a visual analysis perfective.",

keywords = "visual analysis, graph visualisation, graph drawing, coronavirus, COVID-19",

author = "Jie Hua and {Lin Huang}, Mao and Chenglin Zhao and Shuyang Hua and Catherine Shih",

year = "2020",

doi = "10.1109/iv51561.2020.00125",

language = "English",

isbn = "9781728191355",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

pages = "718--722",

editor = "Ebad Banissi and Farzad Khosrow-Shahi and Anna Ursyn and {McK. Bannatyne}, {Mark W.} and Pires, {Jo{\~a}o Moura} and Nuno Datia and Kawa Nazemi and Boris Kovalerchuk and John Counsell and Andrew Agapiou and Zora Vrcelj and Hing-Wah Chau and Mengbi Li and Gehan Nagy and Richard Laing and Rita Francese and Muhammad Sarfraz and Fatma Bouali and Gilles Venturin and Marjan Trutschl and Urska Cvek and Heimo M{\"u}ller and Minoru Nakayama and Marco Temperini and {Di Mascio}, Tania and Filippo Sciarrone and Veronica Rossano and Ralf D{\"o}rner and Loredana Caruccio and Autilia Vitiello and Weidong Huang and Michele Risi and Ugo Erra and Razvan Andonie and Ahmad, {Muhammad Aurangzeb} and Ana Figueiras and Alfredo Cuzzocrea and Mabakane, {Mabule Samuel}",

booktitle = "2020 24th International Conference Information Visualisation (IV)",

address = "United States",

note = "24th International Conference Information Visualisation, IV 2020 ; Conference date: 07-09-2020 Through 11-09-2020",

}

Hua, J, Lin Huang, M, Zhao, C, Hua, S & Shih, C 2020, An initial visual analysis of the relationship between COVID-19 and local community features. in E Banissi, F Khosrow-Shahi, A Ursyn, MW McK. Bannatyne, JM Pires, N Datia, K Nazemi, B Kovalerchuk, J Counsell, A Agapiou, Z Vrcelj, H-W Chau, M Li, G Nagy, R Laing, R Francese, M Sarfraz, F Bouali, G Venturin, M Trutschl, U Cvek, H Müller, M Nakayama, M Temperini, T Di Mascio, F Sciarrone, V Rossano, R Dörner, L Caruccio, A Vitiello, W Huang, M Risi, U Erra, R Andonie, MA Ahmad, A Figueiras, A Cuzzocrea & MS Mabakane (eds), 2020 24th International Conference Information Visualisation (IV). Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ, pp. 718-722, 24th International Conference Information Visualisation, IV 2020, Melbourne, Australia, 7/09/20. https://doi.org/10.1109/iv51561.2020.00125

An initial visual analysis of the relationship between COVID-19 and local community features. / Hua, Jie; Lin Huang, Mao; Zhao, Chenglin et al.
2020 24th International Conference Information Visualisation (IV). ed. / Ebad Banissi; Farzad Khosrow-Shahi; Anna Ursyn; Mark W. McK. Bannatyne; João Moura Pires; Nuno Datia; Kawa Nazemi; Boris Kovalerchuk; John Counsell; Andrew Agapiou; Zora Vrcelj; Hing-Wah Chau; Mengbi Li; Gehan Nagy; Richard Laing; Rita Francese; Muhammad Sarfraz; Fatma Bouali; Gilles Venturin; Marjan Trutschl; Urska Cvek; Heimo Müller; Minoru Nakayama; Marco Temperini; Tania Di Mascio; Filippo Sciarrone; Veronica Rossano; Ralf Dörner; Loredana Caruccio; Autilia Vitiello; Weidong Huang; Michele Risi; Ugo Erra; Razvan Andonie; Muhammad Aurangzeb Ahmad; Ana Figueiras; Alfredo Cuzzocrea; Mabule Samuel Mabakane. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2020. p. 718-722.

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

TY - GEN

T1 - An initial visual analysis of the relationship between COVID-19 and local community features

AU - Hua, Jie

AU - Lin Huang, Mao

AU - Zhao, Chenglin

AU - Hua, Shuyang

AU - Shih, Catherine

PY - 2020

Y1 - 2020

N2 - Virus outbreaks are threats to humanity, and coronaviruses are the latest of many epidemics in the last few decades. In this work, we conduct a non-medical/clinical approach, generating graphs from five features concluded from the COVID-19 outbreak data and local community data in NSW (New South Wales), Australia, and offering insights from a visual analysis perspective The results show that household income, population density and ethnicity affect the infection in different areas. Features such as human behaviours need to be imported for further COVID-19 research in the data science sector. This work is an initial step into this area and allows more insights to be brought into future COVID-19 research through a visual analysis perfective.

AB - Virus outbreaks are threats to humanity, and coronaviruses are the latest of many epidemics in the last few decades. In this work, we conduct a non-medical/clinical approach, generating graphs from five features concluded from the COVID-19 outbreak data and local community data in NSW (New South Wales), Australia, and offering insights from a visual analysis perspective The results show that household income, population density and ethnicity affect the infection in different areas. Features such as human behaviours need to be imported for further COVID-19 research in the data science sector. This work is an initial step into this area and allows more insights to be brought into future COVID-19 research through a visual analysis perfective.

KW - visual analysis

KW - graph visualisation

KW - graph drawing

KW - coronavirus

KW - COVID-19

UR - http://www.scopus.com/inward/record.url?scp=85102923719&partnerID=8YFLogxK

U2 - 10.1109/iv51561.2020.00125

DO - 10.1109/iv51561.2020.00125

M3 - Conference proceeding contribution

SN - 9781728191355

SP - 718

EP - 722

BT - 2020 24th International Conference Information Visualisation (IV)

A2 - Banissi, Ebad

A2 - Khosrow-Shahi, Farzad

A2 - Ursyn, Anna

A2 - McK. Bannatyne, Mark W.

A2 - Pires, João Moura

A2 - Datia, Nuno

A2 - Nazemi, Kawa

A2 - Kovalerchuk, Boris

A2 - Counsell, John

A2 - Agapiou, Andrew

A2 - Vrcelj, Zora

A2 - Chau, Hing-Wah

A2 - Li, Mengbi

A2 - Nagy, Gehan

A2 - Laing, Richard

A2 - Francese, Rita

A2 - Sarfraz, Muhammad

A2 - Bouali, Fatma

A2 - Venturin, Gilles

A2 - Trutschl, Marjan

A2 - Cvek, Urska

A2 - Müller, Heimo

A2 - Nakayama, Minoru

A2 - Temperini, Marco

A2 - Di Mascio, Tania

A2 - Sciarrone, Filippo

A2 - Rossano, Veronica

A2 - Dörner, Ralf

A2 - Caruccio, Loredana

A2 - Vitiello, Autilia

A2 - Huang, Weidong

A2 - Risi, Michele

A2 - Erra, Ugo

A2 - Andonie, Razvan

A2 - Ahmad, Muhammad Aurangzeb

A2 - Figueiras, Ana

A2 - Cuzzocrea, Alfredo

A2 - Mabakane, Mabule Samuel

PB - Institute of Electrical and Electronics Engineers (IEEE)

CY - Piscataway, NJ

T2 - 24th International Conference Information Visualisation, IV 2020

Y2 - 7 September 2020 through 11 September 2020

ER -

Hua J, Lin Huang M, Zhao C, Hua S, Shih C. An initial visual analysis of the relationship between COVID-19 and local community features. In Banissi E, Khosrow-Shahi F, Ursyn A, McK. Bannatyne MW, Pires JM, Datia N, Nazemi K, Kovalerchuk B, Counsell J, Agapiou A, Vrcelj Z, Chau HW, Li M, Nagy G, Laing R, Francese R, Sarfraz M, Bouali F, Venturin G, Trutschl M, Cvek U, Müller H, Nakayama M, Temperini M, Di Mascio T, Sciarrone F, Rossano V, Dörner R, Caruccio L, Vitiello A, Huang W, Risi M, Erra U, Andonie R, Ahmad MA, Figueiras A, Cuzzocrea A, Mabakane MS, editors, 2020 24th International Conference Information Visualisation (IV). Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE). 2020. p. 718-722 doi: 10.1109/iv51561.2020.00125

An initial visual analysis of the relationship between COVID-19 and local community features

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