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COVID-19 mortality dynamics: The future modelled as a (mixture of) past(s)
Discrepancies in population structures, decision making, health systems and numerous other factors result in various COVID-19-mortality dynamics at country scale, and make the forecast of deaths in a country under focus challenging. However, mortality dynamics of countries that are ahead of time imp...
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/PMC7485826/ https://www.ncbi.nlm.nih.gov/pubmed/32915815 http://dx.doi.org/10.1371/journal.pone.0238410 |
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author | Soubeyrand, Samuel Ribaud, Mélina Baudrot, Virgile Allard, Denis Pommeret, Denys Roques, Lionel |
author_facet | Soubeyrand, Samuel Ribaud, Mélina Baudrot, Virgile Allard, Denis Pommeret, Denys Roques, Lionel |
author_sort | Soubeyrand, Samuel |
collection | PubMed |
description | Discrepancies in population structures, decision making, health systems and numerous other factors result in various COVID-19-mortality dynamics at country scale, and make the forecast of deaths in a country under focus challenging. However, mortality dynamics of countries that are ahead of time implicitly include these factors and can be used as real-life competing predicting models. We precisely propose such a data-driven approach implemented in a publicly available web app timely providing mortality curves comparisons and real-time short-term forecasts for about 100 countries. Here, the approach is applied to compare the mortality trajectories of second-line and front-line European countries facing the COVID-19 epidemic wave. Using data up to mid-April, we show that the second-line countries generally followed relatively mild mortality curves rather than fast and severe ones. Thus, the continuation, after mid-April, of the COVID-19 wave across Europe was likely to be mitigated and not as strong as it was in most of the front-line countries first impacted by the wave (this prediction is corroborated by posterior data). |
format | Online Article Text |
id | pubmed-7485826 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-74858262020-09-21 COVID-19 mortality dynamics: The future modelled as a (mixture of) past(s) Soubeyrand, Samuel Ribaud, Mélina Baudrot, Virgile Allard, Denis Pommeret, Denys Roques, Lionel PLoS One Research Article Discrepancies in population structures, decision making, health systems and numerous other factors result in various COVID-19-mortality dynamics at country scale, and make the forecast of deaths in a country under focus challenging. However, mortality dynamics of countries that are ahead of time implicitly include these factors and can be used as real-life competing predicting models. We precisely propose such a data-driven approach implemented in a publicly available web app timely providing mortality curves comparisons and real-time short-term forecasts for about 100 countries. Here, the approach is applied to compare the mortality trajectories of second-line and front-line European countries facing the COVID-19 epidemic wave. Using data up to mid-April, we show that the second-line countries generally followed relatively mild mortality curves rather than fast and severe ones. Thus, the continuation, after mid-April, of the COVID-19 wave across Europe was likely to be mitigated and not as strong as it was in most of the front-line countries first impacted by the wave (this prediction is corroborated by posterior data). Public Library of Science 2020-09-11 /pmc/articles/PMC7485826/ /pubmed/32915815 http://dx.doi.org/10.1371/journal.pone.0238410 Text en © 2020 Soubeyrand 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 Soubeyrand, Samuel Ribaud, Mélina Baudrot, Virgile Allard, Denis Pommeret, Denys Roques, Lionel COVID-19 mortality dynamics: The future modelled as a (mixture of) past(s) |
title | COVID-19 mortality dynamics: The future modelled as a (mixture of) past(s) |
title_full | COVID-19 mortality dynamics: The future modelled as a (mixture of) past(s) |
title_fullStr | COVID-19 mortality dynamics: The future modelled as a (mixture of) past(s) |
title_full_unstemmed | COVID-19 mortality dynamics: The future modelled as a (mixture of) past(s) |
title_short | COVID-19 mortality dynamics: The future modelled as a (mixture of) past(s) |
title_sort | covid-19 mortality dynamics: the future modelled as a (mixture of) past(s) |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7485826/ https://www.ncbi.nlm.nih.gov/pubmed/32915815 http://dx.doi.org/10.1371/journal.pone.0238410 |
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