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Agent-based model for analyzing COVID-19 infection in the campus using AnyLogic software

COVID-19 is a fatal global pandemic that have been spread throughout the world rapidly. Based on the global statistics, the confirmed cases has reached 662 million cases at the mid of June 2021. Typically, COVID-19 is transmitted when a healthy person is closed contact with the infected person via t...

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Main Authors: Gan, W. X., Amerudin, Shahabuddin
Format: Book Section
Published: Springer Science and Business Media Deutschland GmbH 2022
Subjects:
QA76 Computer software
Online Access:http://eprints.utm.my/id/eprint/100935/
http://dx.doi.org/10.1007/978-3-030-94191-8_42
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spelling my.utm.1009352023-05-27T07:38:33Z http://eprints.utm.my/id/eprint/100935/ Agent-based model for analyzing COVID-19 infection in the campus using AnyLogic software Gan, W. X. Amerudin, Shahabuddin QA76 Computer software COVID-19 is a fatal global pandemic that have been spread throughout the world rapidly. Based on the global statistics, the confirmed cases has reached 662 million cases at the mid of June 2021. Typically, COVID-19 is transmitted when a healthy person is closed contact with the infected person via the respiratory droplet or saliva. With the reopening of the academic institution in Malaysia, the formation of new clusters become more seriously. As until 21st April 2021, there are total of 83 COVID-19 clusters is reported that related to the education sector since early January 2021. The students may come back to the campus for conducting academic activities. Therefore, this study is proposed to analyze the COVID-19 infection inside the campus using ABM. The designed ABM model has three different settings, which are lecture room, laboratory and office. Students are the agents of the simulation. The factors of COVID-19 infection are social distance, ventilation condition of the room and exposure time of contact. The ABM model allows the users to analyze the effect of number of people and social distance towards COVID-19 infection. Based on the preliminary analysis, office has the highest risk, followed by lecture room and laboratory. For generating less than 25% of new infected people, the students should maintain at least 1.8 m of social distance. Through the model, the administrators can use to plan the classroom and laboratory to the students. This paper suggests to extend the research by analyzing other rooms in the campus. Springer Science and Business Media Deutschland GmbH 2022 Book Section PeerReviewed Gan, W. X. and Amerudin, Shahabuddin (2022) Agent-based model for analyzing COVID-19 infection in the campus using AnyLogic software. In: Innovations in Smart Cities Applications Volume 5 The Proceedings of the 6th International Conference on Smart City Applications. Lecture Notes in Networks and Systems, 393 (5). Springer Science and Business Media Deutschland GmbH, Cham, Switzerland, pp. 519-530. ISBN 978-303094190-1 http://dx.doi.org/10.1007/978-3-030-94191-8_42 DOI:10.1007/978-3-030-94191-8_42
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic QA76 Computer software
spellingShingle QA76 Computer software
Gan, W. X.
Amerudin, Shahabuddin
Agent-based model for analyzing COVID-19 infection in the campus using AnyLogic software
description COVID-19 is a fatal global pandemic that have been spread throughout the world rapidly. Based on the global statistics, the confirmed cases has reached 662 million cases at the mid of June 2021. Typically, COVID-19 is transmitted when a healthy person is closed contact with the infected person via the respiratory droplet or saliva. With the reopening of the academic institution in Malaysia, the formation of new clusters become more seriously. As until 21st April 2021, there are total of 83 COVID-19 clusters is reported that related to the education sector since early January 2021. The students may come back to the campus for conducting academic activities. Therefore, this study is proposed to analyze the COVID-19 infection inside the campus using ABM. The designed ABM model has three different settings, which are lecture room, laboratory and office. Students are the agents of the simulation. The factors of COVID-19 infection are social distance, ventilation condition of the room and exposure time of contact. The ABM model allows the users to analyze the effect of number of people and social distance towards COVID-19 infection. Based on the preliminary analysis, office has the highest risk, followed by lecture room and laboratory. For generating less than 25% of new infected people, the students should maintain at least 1.8 m of social distance. Through the model, the administrators can use to plan the classroom and laboratory to the students. This paper suggests to extend the research by analyzing other rooms in the campus.
format Book Section
author Gan, W. X.
Amerudin, Shahabuddin
author_facet Gan, W. X.
Amerudin, Shahabuddin
author_sort Gan, W. X.
title Agent-based model for analyzing COVID-19 infection in the campus using AnyLogic software
title_short Agent-based model for analyzing COVID-19 infection in the campus using AnyLogic software
title_full Agent-based model for analyzing COVID-19 infection in the campus using AnyLogic software
title_fullStr Agent-based model for analyzing COVID-19 infection in the campus using AnyLogic software
title_full_unstemmed Agent-based model for analyzing COVID-19 infection in the campus using AnyLogic software
title_sort agent-based model for analyzing covid-19 infection in the campus using anylogic software
publisher Springer Science and Business Media Deutschland GmbH
publishDate 2022
url http://eprints.utm.my/id/eprint/100935/
http://dx.doi.org/10.1007/978-3-030-94191-8_42
_version_ 1768006587126906880
score 13.211869

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