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Agent-based epidemiological modeling of COVID-19 in localized environments()
Epidemiological modeling is used, under certain assumptions, to represent the spread of a disease within a population. Information generated by these models can then be applied to inform public health practices and mitigate risk. To provide useful and actionable preparedness information to administr...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Authors. Published by Elsevier Ltd.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8915620/ https://www.ncbi.nlm.nih.gov/pubmed/35299041 http://dx.doi.org/10.1016/j.compbiomed.2022.105396 |
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author | Ciunkiewicz, P. Brooke, W. Rogers, M. Yanushkevich, S. |
author_facet | Ciunkiewicz, P. Brooke, W. Rogers, M. Yanushkevich, S. |
author_sort | Ciunkiewicz, P. |
collection | PubMed |
description | Epidemiological modeling is used, under certain assumptions, to represent the spread of a disease within a population. Information generated by these models can then be applied to inform public health practices and mitigate risk. To provide useful and actionable preparedness information to administrators and policy makers, epidemiological models must be formulated to model highly localized environments such as office buildings, campuses, or long-term care facilities. In this paper, a highly configurable agent-based simulation (ABS) framework designed for localized environments is proposed. This ABS provides information about risk and the effects of both pharmacological and non-pharmacological interventions, as well as detailed control over the rapidly evolving epidemiological characteristics of COVID-19. Simulation results can inform decisions made by facility administrators and be used as inputs for a complementary decision support system. The application of our ABS to our research lab environment as a proof of concept demonstrates the configurability and insights achievable with this form of modeling, with future work focused on extensibility and integration with decision support. |
format | Online Article Text |
id | pubmed-8915620 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | The Authors. Published by Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-89156202022-03-11 Agent-based epidemiological modeling of COVID-19 in localized environments() Ciunkiewicz, P. Brooke, W. Rogers, M. Yanushkevich, S. Comput Biol Med Article Epidemiological modeling is used, under certain assumptions, to represent the spread of a disease within a population. Information generated by these models can then be applied to inform public health practices and mitigate risk. To provide useful and actionable preparedness information to administrators and policy makers, epidemiological models must be formulated to model highly localized environments such as office buildings, campuses, or long-term care facilities. In this paper, a highly configurable agent-based simulation (ABS) framework designed for localized environments is proposed. This ABS provides information about risk and the effects of both pharmacological and non-pharmacological interventions, as well as detailed control over the rapidly evolving epidemiological characteristics of COVID-19. Simulation results can inform decisions made by facility administrators and be used as inputs for a complementary decision support system. The application of our ABS to our research lab environment as a proof of concept demonstrates the configurability and insights achievable with this form of modeling, with future work focused on extensibility and integration with decision support. The Authors. Published by Elsevier Ltd. 2022-05 2022-03-11 /pmc/articles/PMC8915620/ /pubmed/35299041 http://dx.doi.org/10.1016/j.compbiomed.2022.105396 Text en © 2022 The Authors 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 Ciunkiewicz, P. Brooke, W. Rogers, M. Yanushkevich, S. Agent-based epidemiological modeling of COVID-19 in localized environments() |
title | Agent-based epidemiological modeling of COVID-19 in localized environments() |
title_full | Agent-based epidemiological modeling of COVID-19 in localized environments() |
title_fullStr | Agent-based epidemiological modeling of COVID-19 in localized environments() |
title_full_unstemmed | Agent-based epidemiological modeling of COVID-19 in localized environments() |
title_short | Agent-based epidemiological modeling of COVID-19 in localized environments() |
title_sort | agent-based epidemiological modeling of covid-19 in localized environments() |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8915620/ https://www.ncbi.nlm.nih.gov/pubmed/35299041 http://dx.doi.org/10.1016/j.compbiomed.2022.105396 |
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