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A Parametric Multi-Agent Simulation Framework to Emulate Social Isolation During the Pandemic
Many people worldwide have been at home for months and practicing social distancing to mitigate the spread of coronavirus (COVID-19). What may have started as a single case is now in at least 180 countries. Preliminary surveys indicate that the COVID-19 pandemic has caused people to feel more lonely...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Author(s). Published by Elsevier B.V.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8790958/ https://www.ncbi.nlm.nih.gov/pubmed/35103082 http://dx.doi.org/10.1016/j.procs.2021.12.223 |
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author | Verma, Nimish Zadeh, Pooya Moradian |
author_facet | Verma, Nimish Zadeh, Pooya Moradian |
author_sort | Verma, Nimish |
collection | PubMed |
description | Many people worldwide have been at home for months and practicing social distancing to mitigate the spread of coronavirus (COVID-19). What may have started as a single case is now in at least 180 countries. Preliminary surveys indicate that the COVID-19 pandemic has caused people to feel more lonely and isolated than they did before. It may be due to the fear of the virus, death of loved ones, and the lock-downs restrictions imposed in some countries. This paper proposes a parametric multi-agent simulation framework to emulate Social Isolation during the pandemic. Using the proposed simulator we mimic real-world area of 144 km(2) and population size of 200,000 in order to have near-accurate settings. Various parameters, such as the number of hospitals and capacity, infection rate, recovery, hospitalization, and death, are considered. The simulation is validated on a real-world scale artificial society and is parameterized to a great extent to simulate various settings. |
format | Online Article Text |
id | pubmed-8790958 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | The Author(s). Published by Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-87909582022-01-26 A Parametric Multi-Agent Simulation Framework to Emulate Social Isolation During the Pandemic Verma, Nimish Zadeh, Pooya Moradian Procedia Comput Sci Article Many people worldwide have been at home for months and practicing social distancing to mitigate the spread of coronavirus (COVID-19). What may have started as a single case is now in at least 180 countries. Preliminary surveys indicate that the COVID-19 pandemic has caused people to feel more lonely and isolated than they did before. It may be due to the fear of the virus, death of loved ones, and the lock-downs restrictions imposed in some countries. This paper proposes a parametric multi-agent simulation framework to emulate Social Isolation during the pandemic. Using the proposed simulator we mimic real-world area of 144 km(2) and population size of 200,000 in order to have near-accurate settings. Various parameters, such as the number of hospitals and capacity, infection rate, recovery, hospitalization, and death, are considered. The simulation is validated on a real-world scale artificial society and is parameterized to a great extent to simulate various settings. The Author(s). Published by Elsevier B.V. 2022 2022-01-26 /pmc/articles/PMC8790958/ /pubmed/35103082 http://dx.doi.org/10.1016/j.procs.2021.12.223 Text en © 2021 The Author(s). Published by Elsevier B.V. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Verma, Nimish Zadeh, Pooya Moradian A Parametric Multi-Agent Simulation Framework to Emulate Social Isolation During the Pandemic |
title | A Parametric Multi-Agent Simulation Framework to Emulate Social Isolation During the Pandemic |
title_full | A Parametric Multi-Agent Simulation Framework to Emulate Social Isolation During the Pandemic |
title_fullStr | A Parametric Multi-Agent Simulation Framework to Emulate Social Isolation During the Pandemic |
title_full_unstemmed | A Parametric Multi-Agent Simulation Framework to Emulate Social Isolation During the Pandemic |
title_short | A Parametric Multi-Agent Simulation Framework to Emulate Social Isolation During the Pandemic |
title_sort | parametric multi-agent simulation framework to emulate social isolation during the pandemic |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8790958/ https://www.ncbi.nlm.nih.gov/pubmed/35103082 http://dx.doi.org/10.1016/j.procs.2021.12.223 |
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