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Modelling COVID 19 in the Basque Country from introduction to control measure response
In March 2020, a multidisciplinary task force (so-called Basque Modelling Task Force, BMTF) was created to assist the Basque health managers and Government during the COVID-19 responses. BMTF is a modelling team, working on different approaches, including stochastic processes, statistical methods an...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7560887/ https://www.ncbi.nlm.nih.gov/pubmed/33057119 http://dx.doi.org/10.1038/s41598-020-74386-1 |
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author | Aguiar, Maíra Ortuondo, Eduardo Millán Bidaurrazaga Van-Dierdonck, Joseba Mar, Javier Stollenwerk, Nico |
author_facet | Aguiar, Maíra Ortuondo, Eduardo Millán Bidaurrazaga Van-Dierdonck, Joseba Mar, Javier Stollenwerk, Nico |
author_sort | Aguiar, Maíra |
collection | PubMed |
description | In March 2020, a multidisciplinary task force (so-called Basque Modelling Task Force, BMTF) was created to assist the Basque health managers and Government during the COVID-19 responses. BMTF is a modelling team, working on different approaches, including stochastic processes, statistical methods and artificial intelligence. Here we describe the efforts and challenges to develop a flexible modeling framework able to describe the dynamics observed for the tested positive cases, including the modelling development steps. The results obtained by a new stochastic SHARUCD model framework are presented. Our models differentiate mild and asymptomatic from severe infections prone to be hospitalized and were able to predict the course of the epidemic, providing important projections on the national health system’s necessities during the increased population demand on hospital admissions. Short and longer-term predictions were tested with good results adjusted to the available epidemiological data. We have shown that the partial lockdown measures were effective and enough to slow down disease transmission in the Basque Country. The growth rate [Formula: see text] was calculated from the model and from the data and the implications for the reproduction ratio r are shown. The analysis of the growth rates from the data led to improved model versions describing after the exponential phase also the new information obtained during the phase of response to the control measures. This framework is now being used to monitor disease transmission while the country lockdown was gradually lifted, with insights to specific programs for a general policy of “social distancing” and home quarantining. |
format | Online Article Text |
id | pubmed-7560887 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-75608872020-10-19 Modelling COVID 19 in the Basque Country from introduction to control measure response Aguiar, Maíra Ortuondo, Eduardo Millán Bidaurrazaga Van-Dierdonck, Joseba Mar, Javier Stollenwerk, Nico Sci Rep Article In March 2020, a multidisciplinary task force (so-called Basque Modelling Task Force, BMTF) was created to assist the Basque health managers and Government during the COVID-19 responses. BMTF is a modelling team, working on different approaches, including stochastic processes, statistical methods and artificial intelligence. Here we describe the efforts and challenges to develop a flexible modeling framework able to describe the dynamics observed for the tested positive cases, including the modelling development steps. The results obtained by a new stochastic SHARUCD model framework are presented. Our models differentiate mild and asymptomatic from severe infections prone to be hospitalized and were able to predict the course of the epidemic, providing important projections on the national health system’s necessities during the increased population demand on hospital admissions. Short and longer-term predictions were tested with good results adjusted to the available epidemiological data. We have shown that the partial lockdown measures were effective and enough to slow down disease transmission in the Basque Country. The growth rate [Formula: see text] was calculated from the model and from the data and the implications for the reproduction ratio r are shown. The analysis of the growth rates from the data led to improved model versions describing after the exponential phase also the new information obtained during the phase of response to the control measures. This framework is now being used to monitor disease transmission while the country lockdown was gradually lifted, with insights to specific programs for a general policy of “social distancing” and home quarantining. Nature Publishing Group UK 2020-10-14 /pmc/articles/PMC7560887/ /pubmed/33057119 http://dx.doi.org/10.1038/s41598-020-74386-1 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Aguiar, Maíra Ortuondo, Eduardo Millán Bidaurrazaga Van-Dierdonck, Joseba Mar, Javier Stollenwerk, Nico Modelling COVID 19 in the Basque Country from introduction to control measure response |
title | Modelling COVID 19 in the Basque Country from introduction to control measure response |
title_full | Modelling COVID 19 in the Basque Country from introduction to control measure response |
title_fullStr | Modelling COVID 19 in the Basque Country from introduction to control measure response |
title_full_unstemmed | Modelling COVID 19 in the Basque Country from introduction to control measure response |
title_short | Modelling COVID 19 in the Basque Country from introduction to control measure response |
title_sort | modelling covid 19 in the basque country from introduction to control measure response |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7560887/ https://www.ncbi.nlm.nih.gov/pubmed/33057119 http://dx.doi.org/10.1038/s41598-020-74386-1 |
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