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Using multiagent modeling to forecast the spatiotemporal development of the COVID-19 pandemic in Poland

In the article, the authors present a multi-agent model that simulates the development of the COVID-19 pandemic at the regional level. The developed what-if system is a multi-agent generalization of the SEIR epidemiological model, which enables predicting the pandemic's course in various region...

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Autores principales: Pałka, Piotr, Olszewski, Robert, Kęsik-Brodacka, Małgorzata, Wendland, Agnieszka, Nowak, Karolina, Szczepankowska-Bednarek, Urszula, Liebers, David Th.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9252566/
https://www.ncbi.nlm.nih.gov/pubmed/35789191
http://dx.doi.org/10.1038/s41598-022-15605-9
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author Pałka, Piotr
Olszewski, Robert
Kęsik-Brodacka, Małgorzata
Wendland, Agnieszka
Nowak, Karolina
Szczepankowska-Bednarek, Urszula
Liebers, David Th.
author_facet Pałka, Piotr
Olszewski, Robert
Kęsik-Brodacka, Małgorzata
Wendland, Agnieszka
Nowak, Karolina
Szczepankowska-Bednarek, Urszula
Liebers, David Th.
author_sort Pałka, Piotr
collection PubMed
description In the article, the authors present a multi-agent model that simulates the development of the COVID-19 pandemic at the regional level. The developed what-if system is a multi-agent generalization of the SEIR epidemiological model, which enables predicting the pandemic's course in various regions of Poland, taking into account Poland's spatial and demographic diversity, the residents' level of mobility, and, primarily, the level of restrictions imposed and the associated compliance. The developed simulation system considers detailed topographic data and the residents' professional and private lifestyles specific to the community. A numerical agent represents each resident in the system, thus providing a highly detailed model of social interactions and the pandemic's development. The developed model, made publicly available as free software, was tested in three representative regions of Poland. As the obtained results indicate, implementing social distancing and limiting mobility is crucial for impeding a pandemic before the development of an effective vaccine. It is also essential to consider a given community's social, demographic, and topographic specificity and apply measures appropriate for a given region.
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spelling pubmed-92525662022-07-05 Using multiagent modeling to forecast the spatiotemporal development of the COVID-19 pandemic in Poland Pałka, Piotr Olszewski, Robert Kęsik-Brodacka, Małgorzata Wendland, Agnieszka Nowak, Karolina Szczepankowska-Bednarek, Urszula Liebers, David Th. Sci Rep Article In the article, the authors present a multi-agent model that simulates the development of the COVID-19 pandemic at the regional level. The developed what-if system is a multi-agent generalization of the SEIR epidemiological model, which enables predicting the pandemic's course in various regions of Poland, taking into account Poland's spatial and demographic diversity, the residents' level of mobility, and, primarily, the level of restrictions imposed and the associated compliance. The developed simulation system considers detailed topographic data and the residents' professional and private lifestyles specific to the community. A numerical agent represents each resident in the system, thus providing a highly detailed model of social interactions and the pandemic's development. The developed model, made publicly available as free software, was tested in three representative regions of Poland. As the obtained results indicate, implementing social distancing and limiting mobility is crucial for impeding a pandemic before the development of an effective vaccine. It is also essential to consider a given community's social, demographic, and topographic specificity and apply measures appropriate for a given region. Nature Publishing Group UK 2022-07-04 /pmc/articles/PMC9252566/ /pubmed/35789191 http://dx.doi.org/10.1038/s41598-022-15605-9 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Pałka, Piotr
Olszewski, Robert
Kęsik-Brodacka, Małgorzata
Wendland, Agnieszka
Nowak, Karolina
Szczepankowska-Bednarek, Urszula
Liebers, David Th.
Using multiagent modeling to forecast the spatiotemporal development of the COVID-19 pandemic in Poland
title Using multiagent modeling to forecast the spatiotemporal development of the COVID-19 pandemic in Poland
title_full Using multiagent modeling to forecast the spatiotemporal development of the COVID-19 pandemic in Poland
title_fullStr Using multiagent modeling to forecast the spatiotemporal development of the COVID-19 pandemic in Poland
title_full_unstemmed Using multiagent modeling to forecast the spatiotemporal development of the COVID-19 pandemic in Poland
title_short Using multiagent modeling to forecast the spatiotemporal development of the COVID-19 pandemic in Poland
title_sort using multiagent modeling to forecast the spatiotemporal development of the covid-19 pandemic in poland
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9252566/
https://www.ncbi.nlm.nih.gov/pubmed/35789191
http://dx.doi.org/10.1038/s41598-022-15605-9
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