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COVID-19 pandemic decision support system for a population defense strategy and vaccination effectiveness

The year 2020 ended with a significant COVID-19 pandemic, which traumatized almost many countries where the lockdowns were restored, and numerous emotional social protests erupted. According to the World Health Organization, the global epidemiological situation in the first months of 2021 deteriorat...

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Autores principales: Varotsos, Costas A., Krapivin, Vladimir F., Xue, Yong, Soldatov, Vladimir, Voronova, Tatiana
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8179249/
https://www.ncbi.nlm.nih.gov/pubmed/34108816
http://dx.doi.org/10.1016/j.ssci.2021.105370
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author Varotsos, Costas A.
Krapivin, Vladimir F.
Xue, Yong
Soldatov, Vladimir
Voronova, Tatiana
author_facet Varotsos, Costas A.
Krapivin, Vladimir F.
Xue, Yong
Soldatov, Vladimir
Voronova, Tatiana
author_sort Varotsos, Costas A.
collection PubMed
description The year 2020 ended with a significant COVID-19 pandemic, which traumatized almost many countries where the lockdowns were restored, and numerous emotional social protests erupted. According to the World Health Organization, the global epidemiological situation in the first months of 2021 deteriorated. In this paper, the decision-making supporting system (DMSS) is proposed to be an epidemiological prediction tool. COVID-19 trends in several countries and regions, take into account the big data clouds for important geophysical and socio-ecological characteristics and the expected potentials of the medical service, including vaccination and restrictions on population migration both within the country and international traffic. These parameters for numerical simulations are estimated from officially delivered data that allows the verification of theoretical results. The numerical simulations of the transition and the results of COVID-19 are mainly based on the deterministic approach and the algorithm for processing statistical data based on the instability indicator. DMSS has been shown to help predict the effects of COVID-19 depending on the protection strategies against COVID-19 including vaccination. Numerical simulations have shown that DMSS provides results using accompanying information in the appropriate scenario.
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spelling pubmed-81792492021-06-05 COVID-19 pandemic decision support system for a population defense strategy and vaccination effectiveness Varotsos, Costas A. Krapivin, Vladimir F. Xue, Yong Soldatov, Vladimir Voronova, Tatiana Saf Sci Article The year 2020 ended with a significant COVID-19 pandemic, which traumatized almost many countries where the lockdowns were restored, and numerous emotional social protests erupted. According to the World Health Organization, the global epidemiological situation in the first months of 2021 deteriorated. In this paper, the decision-making supporting system (DMSS) is proposed to be an epidemiological prediction tool. COVID-19 trends in several countries and regions, take into account the big data clouds for important geophysical and socio-ecological characteristics and the expected potentials of the medical service, including vaccination and restrictions on population migration both within the country and international traffic. These parameters for numerical simulations are estimated from officially delivered data that allows the verification of theoretical results. The numerical simulations of the transition and the results of COVID-19 are mainly based on the deterministic approach and the algorithm for processing statistical data based on the instability indicator. DMSS has been shown to help predict the effects of COVID-19 depending on the protection strategies against COVID-19 including vaccination. Numerical simulations have shown that DMSS provides results using accompanying information in the appropriate scenario. Elsevier Ltd. 2021-10 2021-06-05 /pmc/articles/PMC8179249/ /pubmed/34108816 http://dx.doi.org/10.1016/j.ssci.2021.105370 Text en © 2021 Elsevier Ltd. All rights reserved. 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
Varotsos, Costas A.
Krapivin, Vladimir F.
Xue, Yong
Soldatov, Vladimir
Voronova, Tatiana
COVID-19 pandemic decision support system for a population defense strategy and vaccination effectiveness
title COVID-19 pandemic decision support system for a population defense strategy and vaccination effectiveness
title_full COVID-19 pandemic decision support system for a population defense strategy and vaccination effectiveness
title_fullStr COVID-19 pandemic decision support system for a population defense strategy and vaccination effectiveness
title_full_unstemmed COVID-19 pandemic decision support system for a population defense strategy and vaccination effectiveness
title_short COVID-19 pandemic decision support system for a population defense strategy and vaccination effectiveness
title_sort covid-19 pandemic decision support system for a population defense strategy and vaccination effectiveness
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8179249/
https://www.ncbi.nlm.nih.gov/pubmed/34108816
http://dx.doi.org/10.1016/j.ssci.2021.105370
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