Simulating Covid-19 Disease Spread Using Gama Platform to Determine How Disease Prevention Influences the Infection Rate of the Disease

Social distancing is a healthcare practice that helps to keep sick individuals apart from healthy individuals to reduce the risk of disease transmission. This study uses simulation to deliver a realistic representation of a real-life situation. Anyone who is unaware of the realities of a pandemic or...

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Published in:SpringerBriefs in Applied Sciences and Technology
Main Author: Chandran S.; Mohamed N.S.; Zullpakkal N.
Format: Book chapter
Language:English
Published: Springer Science and Business Media Deutschland GmbH 2024
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85192745335&doi=10.1007%2f978-3-031-55558-9_8&partnerID=40&md5=ea8b115fda463a5103d25a17ab608e84
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spelling 2-s2.0-85192745335
Chandran S.; Mohamed N.S.; Zullpakkal N.
Simulating Covid-19 Disease Spread Using Gama Platform to Determine How Disease Prevention Influences the Infection Rate of the Disease
2024
SpringerBriefs in Applied Sciences and Technology
Part F2588

10.1007/978-3-031-55558-9_8
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85192745335&doi=10.1007%2f978-3-031-55558-9_8&partnerID=40&md5=ea8b115fda463a5103d25a17ab608e84
Social distancing is a healthcare practice that helps to keep sick individuals apart from healthy individuals to reduce the risk of disease transmission. This study uses simulation to deliver a realistic representation of a real-life situation. Anyone who is unaware of the realities of a pandemic or how speedily a disease could spread will benefit through a simulation. The objectives of this study are to simulate disease spread using the GAMA platform for two situations that are with and without social distancing and to display the disease spread, graph/chart and the rate of infection within the simulation. People, primarily adults, have been observed to be negligent and perplexed by contemporary discussions, prompting them to second-guess their choices. Most people are unaware of the importance of maintaining social distance everywhere they go. GAMA Platform is used to develop and test the simulation. The simulation contains a calculation for the infection rate as well as a graph to display the changes in population. Through this simulation, the audience get a complete picture and comprehend how being protected impacts the infection rate. As a result, individuals are able to distinguish between how quickly diseases spread with and without social distancing. After testing, the results show that the average number of cycles for the people to get fully infected in a room of 500 people is approximately 28,329 cycles while it took only 8069 cycles with a room of 2500 people. To conclude, when social distancing is enabled, the rate of infection is slower. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Springer Science and Business Media Deutschland GmbH
2191530X
English
Book chapter

author Chandran S.; Mohamed N.S.; Zullpakkal N.
spellingShingle Chandran S.; Mohamed N.S.; Zullpakkal N.
Simulating Covid-19 Disease Spread Using Gama Platform to Determine How Disease Prevention Influences the Infection Rate of the Disease
author_facet Chandran S.; Mohamed N.S.; Zullpakkal N.
author_sort Chandran S.; Mohamed N.S.; Zullpakkal N.
title Simulating Covid-19 Disease Spread Using Gama Platform to Determine How Disease Prevention Influences the Infection Rate of the Disease
title_short Simulating Covid-19 Disease Spread Using Gama Platform to Determine How Disease Prevention Influences the Infection Rate of the Disease
title_full Simulating Covid-19 Disease Spread Using Gama Platform to Determine How Disease Prevention Influences the Infection Rate of the Disease
title_fullStr Simulating Covid-19 Disease Spread Using Gama Platform to Determine How Disease Prevention Influences the Infection Rate of the Disease
title_full_unstemmed Simulating Covid-19 Disease Spread Using Gama Platform to Determine How Disease Prevention Influences the Infection Rate of the Disease
title_sort Simulating Covid-19 Disease Spread Using Gama Platform to Determine How Disease Prevention Influences the Infection Rate of the Disease
publishDate 2024
container_title SpringerBriefs in Applied Sciences and Technology
container_volume Part F2588
container_issue
doi_str_mv 10.1007/978-3-031-55558-9_8
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85192745335&doi=10.1007%2f978-3-031-55558-9_8&partnerID=40&md5=ea8b115fda463a5103d25a17ab608e84
description Social distancing is a healthcare practice that helps to keep sick individuals apart from healthy individuals to reduce the risk of disease transmission. This study uses simulation to deliver a realistic representation of a real-life situation. Anyone who is unaware of the realities of a pandemic or how speedily a disease could spread will benefit through a simulation. The objectives of this study are to simulate disease spread using the GAMA platform for two situations that are with and without social distancing and to display the disease spread, graph/chart and the rate of infection within the simulation. People, primarily adults, have been observed to be negligent and perplexed by contemporary discussions, prompting them to second-guess their choices. Most people are unaware of the importance of maintaining social distance everywhere they go. GAMA Platform is used to develop and test the simulation. The simulation contains a calculation for the infection rate as well as a graph to display the changes in population. Through this simulation, the audience get a complete picture and comprehend how being protected impacts the infection rate. As a result, individuals are able to distinguish between how quickly diseases spread with and without social distancing. After testing, the results show that the average number of cycles for the people to get fully infected in a room of 500 people is approximately 28,329 cycles while it took only 8069 cycles with a room of 2500 people. To conclude, when social distancing is enabled, the rate of infection is slower. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
publisher Springer Science and Business Media Deutschland GmbH
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language English
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