COVID-19: Worldwide profiles during the first 250 days

Detalhes bibliográficos
Autor(a) principal: António, Nuno
Data de Publicação: 2021
Outros Autores: Rita, Paulo, Saraiva, Pedro
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/117162
Resumo: António, N., Rita, P., & Saraiva, P. (2021). COVID-19: Worldwide profiles during the first 250 days. Applied Sciences (Switzerland), 11(8), 1-21. [3400]. https://doi.org/10.3390/app11083400
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spelling COVID-19: Worldwide profiles during the first 250 daysClusteringCOVID-19 pandemicData scienceMachine learningUnsupervised learningMaterials Science(all)InstrumentationEngineering(all)Process Chemistry and TechnologyComputer Science ApplicationsFluid Flow and Transfer ProcessesSDG 3 - Good Health and Well-beingAntónio, N., Rita, P., & Saraiva, P. (2021). COVID-19: Worldwide profiles during the first 250 days. Applied Sciences (Switzerland), 11(8), 1-21. [3400]. https://doi.org/10.3390/app11083400The present COVID-19 pandemic is happening in a strongly interconnected world. This interconnection explains why it became universal in such a short period of time and why it stimulated the creation of a large amount of relevant open data. In this paper, we use data science tools to explore this open data from the moment the pandemic began and across the first 250 days of prevalence before vaccination started. The use of unsupervised machine learning techniques allowed us to identify three clusters of countries and territories with similar profiles of standardized COVID-19 time dynamics. Although countries and territories in the three clusters share some characteristics, their composition is not homogenous. All these clusters contain countries from different geographies and with different development levels. The use of descriptive statistics and data visualization techniques enabled the description and understanding of where and how COVID-19 was impacting. Some interesting extracted features are discussed and suggestions for future research in this area are also presented.Information Management Research Center (MagIC) - NOVA Information Management SchoolNOVA Information Management School (NOVA IMS)RUNAntónio, NunoRita, PauloSaraiva, Pedro2021-05-05T23:28:19Z2021-04-102021-04-10T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article21application/pdfhttp://hdl.handle.net/10362/117162eng2076-3417PURE: 29572045https://doi.org/10.3390/app11083400info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T05:00:14Zoai:run.unl.pt:10362/117162Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:43:30.798618Repositório 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 COVID-19: Worldwide profiles during the first 250 days
title COVID-19: Worldwide profiles during the first 250 days
spellingShingle COVID-19: Worldwide profiles during the first 250 days
António, Nuno
Clustering
COVID-19 pandemic
Data science
Machine learning
Unsupervised learning
Materials Science(all)
Instrumentation
Engineering(all)
Process Chemistry and Technology
Computer Science Applications
Fluid Flow and Transfer Processes
SDG 3 - Good Health and Well-being
title_short COVID-19: Worldwide profiles during the first 250 days
title_full COVID-19: Worldwide profiles during the first 250 days
title_fullStr COVID-19: Worldwide profiles during the first 250 days
title_full_unstemmed COVID-19: Worldwide profiles during the first 250 days
title_sort COVID-19: Worldwide profiles during the first 250 days
author António, Nuno
author_facet António, Nuno
Rita, Paulo
Saraiva, Pedro
author_role author
author2 Rita, Paulo
Saraiva, Pedro
author2_role author
author
dc.contributor.none.fl_str_mv Information Management Research Center (MagIC) - NOVA Information Management School
NOVA Information Management School (NOVA IMS)
RUN
dc.contributor.author.fl_str_mv António, Nuno
Rita, Paulo
Saraiva, Pedro
dc.subject.por.fl_str_mv Clustering
COVID-19 pandemic
Data science
Machine learning
Unsupervised learning
Materials Science(all)
Instrumentation
Engineering(all)
Process Chemistry and Technology
Computer Science Applications
Fluid Flow and Transfer Processes
SDG 3 - Good Health and Well-being
topic Clustering
COVID-19 pandemic
Data science
Machine learning
Unsupervised learning
Materials Science(all)
Instrumentation
Engineering(all)
Process Chemistry and Technology
Computer Science Applications
Fluid Flow and Transfer Processes
SDG 3 - Good Health and Well-being
description António, N., Rita, P., & Saraiva, P. (2021). COVID-19: Worldwide profiles during the first 250 days. Applied Sciences (Switzerland), 11(8), 1-21. [3400]. https://doi.org/10.3390/app11083400
publishDate 2021
dc.date.none.fl_str_mv 2021-05-05T23:28:19Z
2021-04-10
2021-04-10T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/117162
url http://hdl.handle.net/10362/117162
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2076-3417
PURE: 29572045
https://doi.org/10.3390/app11083400
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 21
application/pdf
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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