Cellular Automata in Covid-19 prediction

At the end of 2019 a new coronavirus emerged, turning into a world pandemic. The new coronavirus is called COVID-19. Different countries handled the pandemic differently and our main focus in this article is on Poland. For better counteracting and managing the situation a model for predicting the dy...

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Autores principales: Podolski, Piotr, Nguyen, Hung Son
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Author(s). Published by Elsevier B.V. 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8486235/
https://www.ncbi.nlm.nih.gov/pubmed/34630750
http://dx.doi.org/10.1016/j.procs.2021.09.110
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author Podolski, Piotr
Nguyen, Hung Son
author_facet Podolski, Piotr
Nguyen, Hung Son
author_sort Podolski, Piotr
collection PubMed
description At the end of 2019 a new coronavirus emerged, turning into a world pandemic. The new coronavirus is called COVID-19. Different countries handled the pandemic differently and our main focus in this article is on Poland. For better counteracting and managing the situation a model for predicting the dynamics of the pandemic is needed. In this article we present a model for simulating future infections taking into account various preventive measures and locations in Poland. We based the model on a two-dimensional cellular automata, with spatial dependencies between regions, different population and size of simulated regions.
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spelling pubmed-84862352021-10-04 Cellular Automata in Covid-19 prediction Podolski, Piotr Nguyen, Hung Son Procedia Comput Sci Article At the end of 2019 a new coronavirus emerged, turning into a world pandemic. The new coronavirus is called COVID-19. Different countries handled the pandemic differently and our main focus in this article is on Poland. For better counteracting and managing the situation a model for predicting the dynamics of the pandemic is needed. In this article we present a model for simulating future infections taking into account various preventive measures and locations in Poland. We based the model on a two-dimensional cellular automata, with spatial dependencies between regions, different population and size of simulated regions. The Author(s). Published by Elsevier B.V. 2021 2021-10-01 /pmc/articles/PMC8486235/ /pubmed/34630750 http://dx.doi.org/10.1016/j.procs.2021.09.110 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
Podolski, Piotr
Nguyen, Hung Son
Cellular Automata in Covid-19 prediction
title Cellular Automata in Covid-19 prediction
title_full Cellular Automata in Covid-19 prediction
title_fullStr Cellular Automata in Covid-19 prediction
title_full_unstemmed Cellular Automata in Covid-19 prediction
title_short Cellular Automata in Covid-19 prediction
title_sort cellular automata in covid-19 prediction
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8486235/
https://www.ncbi.nlm.nih.gov/pubmed/34630750
http://dx.doi.org/10.1016/j.procs.2021.09.110
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