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Understanding the cycles of COVID-19 incidence: Principal Component Analysis and interaction of biological and socio-economic factors
The incidence curve of coronavirus disease 19 (COVID-19) shows cyclical patterns over time. We examine the cyclical properties of the incidence curves in various countries and use principal components analysis to shed light on the underlying dynamics that are common to all countries. We find that th...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8168336/ https://www.ncbi.nlm.nih.gov/pubmed/34094532 http://dx.doi.org/10.1016/j.amsu.2021.102437 |
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author | Duarte, Pablo Riveros-Perez, Efrain |
author_facet | Duarte, Pablo Riveros-Perez, Efrain |
author_sort | Duarte, Pablo |
collection | PubMed |
description | The incidence curve of coronavirus disease 19 (COVID-19) shows cyclical patterns over time. We examine the cyclical properties of the incidence curves in various countries and use principal components analysis to shed light on the underlying dynamics that are common to all countries. We find that the cyclical series of 37 countries can be summarized in four principal components which explain over 90% of the variation. We also discuss the influence of complex interactions between biological viral natural history and socio-political reactions and measures adopted by different countries on the cyclical patterns exhibited by COVID-19 around the globe. |
format | Online Article Text |
id | pubmed-8168336 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-81683362021-06-01 Understanding the cycles of COVID-19 incidence: Principal Component Analysis and interaction of biological and socio-economic factors Duarte, Pablo Riveros-Perez, Efrain Ann Med Surg (Lond) Experimental Research The incidence curve of coronavirus disease 19 (COVID-19) shows cyclical patterns over time. We examine the cyclical properties of the incidence curves in various countries and use principal components analysis to shed light on the underlying dynamics that are common to all countries. We find that the cyclical series of 37 countries can be summarized in four principal components which explain over 90% of the variation. We also discuss the influence of complex interactions between biological viral natural history and socio-political reactions and measures adopted by different countries on the cyclical patterns exhibited by COVID-19 around the globe. Elsevier 2021-06-01 /pmc/articles/PMC8168336/ /pubmed/34094532 http://dx.doi.org/10.1016/j.amsu.2021.102437 Text en © 2021 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Experimental Research Duarte, Pablo Riveros-Perez, Efrain Understanding the cycles of COVID-19 incidence: Principal Component Analysis and interaction of biological and socio-economic factors |
title | Understanding the cycles of COVID-19 incidence: Principal Component Analysis and interaction of biological and socio-economic factors |
title_full | Understanding the cycles of COVID-19 incidence: Principal Component Analysis and interaction of biological and socio-economic factors |
title_fullStr | Understanding the cycles of COVID-19 incidence: Principal Component Analysis and interaction of biological and socio-economic factors |
title_full_unstemmed | Understanding the cycles of COVID-19 incidence: Principal Component Analysis and interaction of biological and socio-economic factors |
title_short | Understanding the cycles of COVID-19 incidence: Principal Component Analysis and interaction of biological and socio-economic factors |
title_sort | understanding the cycles of covid-19 incidence: principal component analysis and interaction of biological and socio-economic factors |
topic | Experimental Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8168336/ https://www.ncbi.nlm.nih.gov/pubmed/34094532 http://dx.doi.org/10.1016/j.amsu.2021.102437 |
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