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Empirical model for short-time prediction of COVID-19 spreading

The appearance and fast spreading of Covid-19 took the international community by surprise. Collaboration between researchers, public health workers, and politicians has been established to deal with the epidemic. One important contribution from researchers in epidemiology is the analysis of trends...

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Autores principales: Català, Martí, Alonso, Sergio, Alvarez-Lacalle, Enrique, López, Daniel, Cardona, Pere-Joan, Prats, Clara
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7725384/
https://www.ncbi.nlm.nih.gov/pubmed/33296373
http://dx.doi.org/10.1371/journal.pcbi.1008431
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author Català, Martí
Alonso, Sergio
Alvarez-Lacalle, Enrique
López, Daniel
Cardona, Pere-Joan
Prats, Clara
author_facet Català, Martí
Alonso, Sergio
Alvarez-Lacalle, Enrique
López, Daniel
Cardona, Pere-Joan
Prats, Clara
author_sort Català, Martí
collection PubMed
description The appearance and fast spreading of Covid-19 took the international community by surprise. Collaboration between researchers, public health workers, and politicians has been established to deal with the epidemic. One important contribution from researchers in epidemiology is the analysis of trends so that both the current state and short-term future trends can be carefully evaluated. Gompertz model has been shown to correctly describe the dynamics of cumulative confirmed cases, since it is characterized by a decrease in growth rate showing the effect of control measures. Thus, it provides a way to systematically quantify the Covid-19 spreading velocity and it allows short-term predictions and longer-term estimations. This model has been employed to fit the cumulative cases of Covid-19 from several European countries. Results show that there are systematic differences in spreading velocity among countries. The model predictions provide a reliable picture of the short-term evolution in countries that are in the initial stages of the Covid-19 outbreak, and may permit researchers to uncover some characteristics of the long-term evolution. These predictions can also be generalized to calculate short-term hospital and intensive care units (ICU) requirements.
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spelling pubmed-77253842020-12-16 Empirical model for short-time prediction of COVID-19 spreading Català, Martí Alonso, Sergio Alvarez-Lacalle, Enrique López, Daniel Cardona, Pere-Joan Prats, Clara PLoS Comput Biol Research Article The appearance and fast spreading of Covid-19 took the international community by surprise. Collaboration between researchers, public health workers, and politicians has been established to deal with the epidemic. One important contribution from researchers in epidemiology is the analysis of trends so that both the current state and short-term future trends can be carefully evaluated. Gompertz model has been shown to correctly describe the dynamics of cumulative confirmed cases, since it is characterized by a decrease in growth rate showing the effect of control measures. Thus, it provides a way to systematically quantify the Covid-19 spreading velocity and it allows short-term predictions and longer-term estimations. This model has been employed to fit the cumulative cases of Covid-19 from several European countries. Results show that there are systematic differences in spreading velocity among countries. The model predictions provide a reliable picture of the short-term evolution in countries that are in the initial stages of the Covid-19 outbreak, and may permit researchers to uncover some characteristics of the long-term evolution. These predictions can also be generalized to calculate short-term hospital and intensive care units (ICU) requirements. Public Library of Science 2020-12-09 /pmc/articles/PMC7725384/ /pubmed/33296373 http://dx.doi.org/10.1371/journal.pcbi.1008431 Text en © 2020 Català et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Català, Martí
Alonso, Sergio
Alvarez-Lacalle, Enrique
López, Daniel
Cardona, Pere-Joan
Prats, Clara
Empirical model for short-time prediction of COVID-19 spreading
title Empirical model for short-time prediction of COVID-19 spreading
title_full Empirical model for short-time prediction of COVID-19 spreading
title_fullStr Empirical model for short-time prediction of COVID-19 spreading
title_full_unstemmed Empirical model for short-time prediction of COVID-19 spreading
title_short Empirical model for short-time prediction of COVID-19 spreading
title_sort empirical model for short-time prediction of covid-19 spreading
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7725384/
https://www.ncbi.nlm.nih.gov/pubmed/33296373
http://dx.doi.org/10.1371/journal.pcbi.1008431
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