A differential equations model-fitting analysis of COVID-19 epidemiological data to explain multi-wave dynamics

Abstract Compartmental epidemiological models are, by far, the most popular in the study of dynamics related with infectious diseases. It is, therefore, not surprising that they are frequently used to study the current COVID-19 pandemic. Taking advantage of the real-time availability of COVID-19 rel...

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Autores principales:	Maria Jardim Beira, Pedro José Sebastião
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/19b3ed07e4b2433eb2322e6c953f380a
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id	oai:doaj.org-article:19b3ed07e4b2433eb2322e6c953f380a
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spelling	oai:doaj.org-article:19b3ed07e4b2433eb2322e6c953f380a2021-12-02T19:06:42ZA differential equations model-fitting analysis of COVID-19 epidemiological data to explain multi-wave dynamics10.1038/s41598-021-95494-62045-2322https://doaj.org/article/19b3ed07e4b2433eb2322e6c953f380a2021-08-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-95494-6https://doaj.org/toc/2045-2322Abstract Compartmental epidemiological models are, by far, the most popular in the study of dynamics related with infectious diseases. It is, therefore, not surprising that they are frequently used to study the current COVID-19 pandemic. Taking advantage of the real-time availability of COVID-19 related data, we perform a compartmental model fitting analysis of the portuguese case, using an online open-access platform with the integrated capability of solving systems of differential equations. This analysis enabled the data-driven validation of the used model and was the basis for robust projections of different future scenarios, namely, increasing the detected infected population, reopening schools at different moments, allowing Easter celebrations to take place and population vaccination. The method presented in this work can easily be used to perform the non-trivial task of simultaneously fitting differential equation solutions to different epidemiological data sets, regardless of the model or country that might be considered in the analysis.Maria Jardim BeiraPedro José SebastiãoNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-13 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Maria Jardim Beira Pedro José Sebastião A differential equations model-fitting analysis of COVID-19 epidemiological data to explain multi-wave dynamics
description	Abstract Compartmental epidemiological models are, by far, the most popular in the study of dynamics related with infectious diseases. It is, therefore, not surprising that they are frequently used to study the current COVID-19 pandemic. Taking advantage of the real-time availability of COVID-19 related data, we perform a compartmental model fitting analysis of the portuguese case, using an online open-access platform with the integrated capability of solving systems of differential equations. This analysis enabled the data-driven validation of the used model and was the basis for robust projections of different future scenarios, namely, increasing the detected infected population, reopening schools at different moments, allowing Easter celebrations to take place and population vaccination. The method presented in this work can easily be used to perform the non-trivial task of simultaneously fitting differential equation solutions to different epidemiological data sets, regardless of the model or country that might be considered in the analysis.
format	article
author	Maria Jardim Beira Pedro José Sebastião
author_facet	Maria Jardim Beira Pedro José Sebastião
author_sort	Maria Jardim Beira
title	A differential equations model-fitting analysis of COVID-19 epidemiological data to explain multi-wave dynamics
title_short	A differential equations model-fitting analysis of COVID-19 epidemiological data to explain multi-wave dynamics
title_full	A differential equations model-fitting analysis of COVID-19 epidemiological data to explain multi-wave dynamics
title_fullStr	A differential equations model-fitting analysis of COVID-19 epidemiological data to explain multi-wave dynamics
title_full_unstemmed	A differential equations model-fitting analysis of COVID-19 epidemiological data to explain multi-wave dynamics
title_sort	differential equations model-fitting analysis of covid-19 epidemiological data to explain multi-wave dynamics
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/19b3ed07e4b2433eb2322e6c953f380a
work_keys_str_mv	AT mariajardimbeira adifferentialequationsmodelfittinganalysisofcovid19epidemiologicaldatatoexplainmultiwavedynamics AT pedrojosesebastiao adifferentialequationsmodelfittinganalysisofcovid19epidemiologicaldatatoexplainmultiwavedynamics AT mariajardimbeira differentialequationsmodelfittinganalysisofcovid19epidemiologicaldatatoexplainmultiwavedynamics AT pedrojosesebastiao differentialequationsmodelfittinganalysisofcovid19epidemiologicaldatatoexplainmultiwavedynamics
_version_	1718377133583106048

A differential equations model-fitting analysis of COVID-19 epidemiological data to explain multi-wave dynamics

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