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The growth of COVID-19 in Spain. A view based on time-series forecasting methods
The current COVID-19 crisis has required the scientific community to use different approaches to analyze and understand the pattern of the pandemic's evolution. Spain is one of the most affected countries in Europe. It has suffered heavily, with thousands of deaths, and a highly stressful situa...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8137980/ http://dx.doi.org/10.1016/B978-0-12-824536-1.00020-4 |
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author | Carrión-García, Andrés Jabaloyes, José Grisales, Angela |
author_facet | Carrión-García, Andrés Jabaloyes, José Grisales, Angela |
author_sort | Carrión-García, Andrés |
collection | PubMed |
description | The current COVID-19 crisis has required the scientific community to use different approaches to analyze and understand the pattern of the pandemic's evolution. Spain is one of the most affected countries in Europe. It has suffered heavily, with thousands of deaths, and a highly stressful situation that has affected the country's health system and all facets of day-to-day life. The period considered in the analysis runs from March 4, the date of the first official COVID-19 death, to April 7, which can be considered as the end of the pandemic's growth phase. The approach used in the study is time-series analysis, a statistical tool that explores the underlying inertia in the development of social, physical, or natural phenomena to predict their future evolution. ARIMA models have been applied. Accurate prediction models have been obtained, and the relationship between some of the time series used has been identified. |
format | Online Article Text |
id | pubmed-8137980 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
record_format | MEDLINE/PubMed |
spelling | pubmed-81379802021-05-21 The growth of COVID-19 in Spain. A view based on time-series forecasting methods Carrión-García, Andrés Jabaloyes, José Grisales, Angela Data Science for COVID-19 Article The current COVID-19 crisis has required the scientific community to use different approaches to analyze and understand the pattern of the pandemic's evolution. Spain is one of the most affected countries in Europe. It has suffered heavily, with thousands of deaths, and a highly stressful situation that has affected the country's health system and all facets of day-to-day life. The period considered in the analysis runs from March 4, the date of the first official COVID-19 death, to April 7, which can be considered as the end of the pandemic's growth phase. The approach used in the study is time-series analysis, a statistical tool that explores the underlying inertia in the development of social, physical, or natural phenomena to predict their future evolution. ARIMA models have been applied. Accurate prediction models have been obtained, and the relationship between some of the time series used has been identified. 2021 2021-05-21 /pmc/articles/PMC8137980/ http://dx.doi.org/10.1016/B978-0-12-824536-1.00020-4 Text en Copyright © 2021 Elsevier Inc. 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 Carrión-García, Andrés Jabaloyes, José Grisales, Angela The growth of COVID-19 in Spain. A view based on time-series forecasting methods |
title | The growth of COVID-19 in Spain. A view based on time-series forecasting methods |
title_full | The growth of COVID-19 in Spain. A view based on time-series forecasting methods |
title_fullStr | The growth of COVID-19 in Spain. A view based on time-series forecasting methods |
title_full_unstemmed | The growth of COVID-19 in Spain. A view based on time-series forecasting methods |
title_short | The growth of COVID-19 in Spain. A view based on time-series forecasting methods |
title_sort | growth of covid-19 in spain. a view based on time-series forecasting methods |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8137980/ http://dx.doi.org/10.1016/B978-0-12-824536-1.00020-4 |
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