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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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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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. |
format | Online Article Text |
id | pubmed-7725384 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
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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