Abstract
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.
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Acknowledgements
We would like to express our gratitude to the MOHE and UTM for their financial support in the research grant Vot Number Q.J130000.3852.19J13.
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Gan, W.X., Amerudin, S. (2022). Agent-Based Model for Analyzing COVID-19 Infection in the Campus Using AnyLogic Software. In: Ben Ahmed, M., Boudhir, A.A., Karaș, İ.R., Jain, V., Mellouli, S. (eds) Innovations in Smart Cities Applications Volume 5. SCA 2021. Lecture Notes in Networks and Systems, vol 393. Springer, Cham. https://doi.org/10.1007/978-3-030-94191-8_42
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