Rare and extreme events: the case of COVID-19 pandemic

Detalhes bibliográficos
Autor(a) principal: Tenreiro Machado, J. A.
Data de Publicação: 2020
Outros Autores: Lopes, António M.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.22/22480
Resumo: Complex systems have characteristics that give rise to the emergence of rare and extreme events. This paper addresses an example of such type of crisis, namely the spread of the new Coronavirus disease 2019 (COVID-19). The study deals with the statistical comparison and visualization of country-based real-data for the period December 31, 2019, up to April 12, 2020, and does not intend to address the medical treatment of the disease. Two distinct approaches are considered, the description of the number of infected people across time by means of heuristic models fitting the real-world data, and the comparison of countries based on hierarchical clustering and multidimensional scaling. The computational and mathematical modeling lead to the emergence of patterns, highlighting similarities and differences between the countries, pointing toward the main characteristics of the complex dynamics.
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spelling Rare and extreme events: the case of COVID-19 pandemicCoronavirus disease 2019Extreme eventsRegressionMultidimensional scalingHierarchical clusteringComplex systemsComplex systems have characteristics that give rise to the emergence of rare and extreme events. This paper addresses an example of such type of crisis, namely the spread of the new Coronavirus disease 2019 (COVID-19). The study deals with the statistical comparison and visualization of country-based real-data for the period December 31, 2019, up to April 12, 2020, and does not intend to address the medical treatment of the disease. Two distinct approaches are considered, the description of the number of infected people across time by means of heuristic models fitting the real-world data, and the comparison of countries based on hierarchical clustering and multidimensional scaling. The computational and mathematical modeling lead to the emergence of patterns, highlighting similarities and differences between the countries, pointing toward the main characteristics of the complex dynamics.SpringerRepositório Científico do Instituto Politécnico do PortoTenreiro Machado, J. A.Lopes, António M.20202035-01-01T00:00:00Z2020-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.22/22480eng0924-090X10.1007/s11071-020-05680-winfo:eu-repo/semantics/embargoedAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-03-22T01:46:51Zoai:recipp.ipp.pt:10400.22/22480Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:42:33.985122Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Rare and extreme events: the case of COVID-19 pandemic
title Rare and extreme events: the case of COVID-19 pandemic
spellingShingle Rare and extreme events: the case of COVID-19 pandemic
Tenreiro Machado, J. A.
Coronavirus disease 2019
Extreme events
Regression
Multidimensional scaling
Hierarchical clustering
Complex systems
title_short Rare and extreme events: the case of COVID-19 pandemic
title_full Rare and extreme events: the case of COVID-19 pandemic
title_fullStr Rare and extreme events: the case of COVID-19 pandemic
title_full_unstemmed Rare and extreme events: the case of COVID-19 pandemic
title_sort Rare and extreme events: the case of COVID-19 pandemic
author Tenreiro Machado, J. A.
author_facet Tenreiro Machado, J. A.
Lopes, António M.
author_role author
author2 Lopes, António M.
author2_role author
dc.contributor.none.fl_str_mv Repositório Científico do Instituto Politécnico do Porto
dc.contributor.author.fl_str_mv Tenreiro Machado, J. A.
Lopes, António M.
dc.subject.por.fl_str_mv Coronavirus disease 2019
Extreme events
Regression
Multidimensional scaling
Hierarchical clustering
Complex systems
topic Coronavirus disease 2019
Extreme events
Regression
Multidimensional scaling
Hierarchical clustering
Complex systems
description Complex systems have characteristics that give rise to the emergence of rare and extreme events. This paper addresses an example of such type of crisis, namely the spread of the new Coronavirus disease 2019 (COVID-19). The study deals with the statistical comparison and visualization of country-based real-data for the period December 31, 2019, up to April 12, 2020, and does not intend to address the medical treatment of the disease. Two distinct approaches are considered, the description of the number of infected people across time by means of heuristic models fitting the real-world data, and the comparison of countries based on hierarchical clustering and multidimensional scaling. The computational and mathematical modeling lead to the emergence of patterns, highlighting similarities and differences between the countries, pointing toward the main characteristics of the complex dynamics.
publishDate 2020
dc.date.none.fl_str_mv 2020
2020-01-01T00:00:00Z
2035-01-01T00:00:00Z
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10.1007/s11071-020-05680-w
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