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Application of probabilistic models for extreme values to the COVID-2019 epidemic daily dataset
Worldwide, COVID-19 coronavirus disease is spreading rapidly in a second and third wave of infections. In this context of increasing infections, it is critical to know the probability of a specific number of cases being reported. We collated data on new daily confirmed cases of COVID-19 breakouts in...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8719919/ https://www.ncbi.nlm.nih.gov/pubmed/35005154 http://dx.doi.org/10.1016/j.dib.2021.107783 |
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author | Canton Enriquez, Daniel Niembro-Ceceña, Jose A. Muñoz Mandujano, Martin Alarcon, Daniel Arcadia Guerrero, Jorge Gonzalez Garcia, Ivan Montes Gutierrez, Agueda Areli Gutierrez-Lopez, Alfonso |
author_facet | Canton Enriquez, Daniel Niembro-Ceceña, Jose A. Muñoz Mandujano, Martin Alarcon, Daniel Arcadia Guerrero, Jorge Gonzalez Garcia, Ivan Montes Gutierrez, Agueda Areli Gutierrez-Lopez, Alfonso |
author_sort | Canton Enriquez, Daniel |
collection | PubMed |
description | Worldwide, COVID-19 coronavirus disease is spreading rapidly in a second and third wave of infections. In this context of increasing infections, it is critical to know the probability of a specific number of cases being reported. We collated data on new daily confirmed cases of COVID-19 breakouts in: Argentina, Brazil, China, Colombia, France, Germany, India, Indonesia, Iran, Italy, Mexico, Poland, Russia, Spain, U.K., and the United States, from the 20th of January, 2020 to 28th of August 2021. A selected sample of almost ten thousand data is used to validate the proposed models. Generalized Extreme-Value Distribution Type 1-Gumbel and Exponential (1, 2 parameters) models were introduced to analyze the probability of new daily confirmed cases. The data presented in this document for each country provide the daily probability of rate incidence. In addition, the frequencies of historical events expressed as a return period in days of the complete data set is provided. |
format | Online Article Text |
id | pubmed-8719919 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-87199192022-01-03 Application of probabilistic models for extreme values to the COVID-2019 epidemic daily dataset Canton Enriquez, Daniel Niembro-Ceceña, Jose A. Muñoz Mandujano, Martin Alarcon, Daniel Arcadia Guerrero, Jorge Gonzalez Garcia, Ivan Montes Gutierrez, Agueda Areli Gutierrez-Lopez, Alfonso Data Brief Data Article Worldwide, COVID-19 coronavirus disease is spreading rapidly in a second and third wave of infections. In this context of increasing infections, it is critical to know the probability of a specific number of cases being reported. We collated data on new daily confirmed cases of COVID-19 breakouts in: Argentina, Brazil, China, Colombia, France, Germany, India, Indonesia, Iran, Italy, Mexico, Poland, Russia, Spain, U.K., and the United States, from the 20th of January, 2020 to 28th of August 2021. A selected sample of almost ten thousand data is used to validate the proposed models. Generalized Extreme-Value Distribution Type 1-Gumbel and Exponential (1, 2 parameters) models were introduced to analyze the probability of new daily confirmed cases. The data presented in this document for each country provide the daily probability of rate incidence. In addition, the frequencies of historical events expressed as a return period in days of the complete data set is provided. Elsevier 2022-01-01 /pmc/articles/PMC8719919/ /pubmed/35005154 http://dx.doi.org/10.1016/j.dib.2021.107783 Text en © 2022 The Authors. Published by Elsevier Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Data Article Canton Enriquez, Daniel Niembro-Ceceña, Jose A. Muñoz Mandujano, Martin Alarcon, Daniel Arcadia Guerrero, Jorge Gonzalez Garcia, Ivan Montes Gutierrez, Agueda Areli Gutierrez-Lopez, Alfonso Application of probabilistic models for extreme values to the COVID-2019 epidemic daily dataset |
title | Application of probabilistic models for extreme values to the COVID-2019 epidemic daily dataset |
title_full | Application of probabilistic models for extreme values to the COVID-2019 epidemic daily dataset |
title_fullStr | Application of probabilistic models for extreme values to the COVID-2019 epidemic daily dataset |
title_full_unstemmed | Application of probabilistic models for extreme values to the COVID-2019 epidemic daily dataset |
title_short | Application of probabilistic models for extreme values to the COVID-2019 epidemic daily dataset |
title_sort | application of probabilistic models for extreme values to the covid-2019 epidemic daily dataset |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8719919/ https://www.ncbi.nlm.nih.gov/pubmed/35005154 http://dx.doi.org/10.1016/j.dib.2021.107783 |
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