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Enhancing resilience in construction against infectious diseases using stochastic multi-agent approach
To recover from the adverse impacts of COVID-19 on construction and to avoid further losses to the industry in future pandemics, the resilience of construction industry needs to be enhanced against infectious diseases. Currently, there is a gap for modelling frameworks to simulate the spread of infe...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Author. Published by Elsevier B.V.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9091540/ https://www.ncbi.nlm.nih.gov/pubmed/35573273 http://dx.doi.org/10.1016/j.autcon.2022.104315 |
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author | Gerami Seresht, Nima |
author_facet | Gerami Seresht, Nima |
author_sort | Gerami Seresht, Nima |
collection | PubMed |
description | To recover from the adverse impacts of COVID-19 on construction and to avoid further losses to the industry in future pandemics, the resilience of construction industry needs to be enhanced against infectious diseases. Currently, there is a gap for modelling frameworks to simulate the spread of infectious diseases in construction projects at micro-level and to test interventions' effectiveness for data-informed decision-making. Here, this gap is addressed by developing a simulation framework using stochastic agent-based modelling, which enables construction researchers and practitioners to simulate and limit the spread of infectious diseases in construction projects. This is specifically important, since the results of a building project case-study reveals that, in comparison to the general population, infectious diseases may spread faster among construction workers and fatalities can be significantly higher. The proposed framework motivates future research on micro-level modelling of infectious diseases and efforts for intervening the spread of diseases in construction projects. |
format | Online Article Text |
id | pubmed-9091540 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | The Author. Published by Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-90915402022-05-11 Enhancing resilience in construction against infectious diseases using stochastic multi-agent approach Gerami Seresht, Nima Autom Constr Article To recover from the adverse impacts of COVID-19 on construction and to avoid further losses to the industry in future pandemics, the resilience of construction industry needs to be enhanced against infectious diseases. Currently, there is a gap for modelling frameworks to simulate the spread of infectious diseases in construction projects at micro-level and to test interventions' effectiveness for data-informed decision-making. Here, this gap is addressed by developing a simulation framework using stochastic agent-based modelling, which enables construction researchers and practitioners to simulate and limit the spread of infectious diseases in construction projects. This is specifically important, since the results of a building project case-study reveals that, in comparison to the general population, infectious diseases may spread faster among construction workers and fatalities can be significantly higher. The proposed framework motivates future research on micro-level modelling of infectious diseases and efforts for intervening the spread of diseases in construction projects. The Author. Published by Elsevier B.V. 2022-08 2022-05-11 /pmc/articles/PMC9091540/ /pubmed/35573273 http://dx.doi.org/10.1016/j.autcon.2022.104315 Text en © 2022 The Author 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 Gerami Seresht, Nima Enhancing resilience in construction against infectious diseases using stochastic multi-agent approach |
title | Enhancing resilience in construction against infectious diseases using stochastic multi-agent approach |
title_full | Enhancing resilience in construction against infectious diseases using stochastic multi-agent approach |
title_fullStr | Enhancing resilience in construction against infectious diseases using stochastic multi-agent approach |
title_full_unstemmed | Enhancing resilience in construction against infectious diseases using stochastic multi-agent approach |
title_short | Enhancing resilience in construction against infectious diseases using stochastic multi-agent approach |
title_sort | enhancing resilience in construction against infectious diseases using stochastic multi-agent approach |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9091540/ https://www.ncbi.nlm.nih.gov/pubmed/35573273 http://dx.doi.org/10.1016/j.autcon.2022.104315 |
work_keys_str_mv | AT geramisereshtnima enhancingresilienceinconstructionagainstinfectiousdiseasesusingstochasticmultiagentapproach |