Reliably quantifying the evolving worldwide dynamic state of the COVID-19 outbreak from death records, clinical parametrization, and demographic data

Abstract The dynamic characterization of the COVID-19 outbreak is critical to implement effective actions for its control and eradication but the information available at a global scale is not sufficiently reliable to be used directly. Here, we develop a quantitative approach to reliably quantify it...

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Main Authors: Jose M. G. Vilar, Leonor Saiz
Format: Article
Language:English
Published: Nature Publishing Group 2021-10-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-021-99273-1
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spelling doaj-ac0984a696b64e4ea31d3b8130c6e41a2021-10-10T11:27:36ZengNature Publishing GroupScientific Reports2045-23222021-10-0111111510.1038/s41598-021-99273-1Reliably quantifying the evolving worldwide dynamic state of the COVID-19 outbreak from death records, clinical parametrization, and demographic dataJose M. G. Vilar0Leonor Saiz1Biofisika Institute (CSIC, UPV/EHU), University of the Basque Country (UPV/EHU)Department of Biomedical Engineering, University of CaliforniaAbstract The dynamic characterization of the COVID-19 outbreak is critical to implement effective actions for its control and eradication but the information available at a global scale is not sufficiently reliable to be used directly. Here, we develop a quantitative approach to reliably quantify its temporal evolution and controllability through the integration of multiple data sources, including death records, clinical parametrization of the disease, and demographic data, and we explicitly apply it to countries worldwide, covering 97.4% of the human population, and to states within the United States (US). The validation of the approach shows that it can accurately reproduce the available prevalence data and that it can precisely infer the timing of nonpharmaceutical interventions. The results of the analysis identified general patterns of recession, stabilization, and resurgence. The diversity of dynamic behaviors of the outbreak across countries is paralleled by those of states and territories in the US, converging to remarkably similar global states in both cases. Our results offer precise insights into the dynamics of the outbreak and an efficient avenue for the estimation of the prevalence rates over time.https://doi.org/10.1038/s41598-021-99273-1
collection DOAJ
language English
format Article
sources DOAJ
author Jose M. G. Vilar
Leonor Saiz
spellingShingle Jose M. G. Vilar
Leonor Saiz
Reliably quantifying the evolving worldwide dynamic state of the COVID-19 outbreak from death records, clinical parametrization, and demographic data
Scientific Reports
author_facet Jose M. G. Vilar
Leonor Saiz
author_sort Jose M. G. Vilar
title Reliably quantifying the evolving worldwide dynamic state of the COVID-19 outbreak from death records, clinical parametrization, and demographic data
title_short Reliably quantifying the evolving worldwide dynamic state of the COVID-19 outbreak from death records, clinical parametrization, and demographic data
title_full Reliably quantifying the evolving worldwide dynamic state of the COVID-19 outbreak from death records, clinical parametrization, and demographic data
title_fullStr Reliably quantifying the evolving worldwide dynamic state of the COVID-19 outbreak from death records, clinical parametrization, and demographic data
title_full_unstemmed Reliably quantifying the evolving worldwide dynamic state of the COVID-19 outbreak from death records, clinical parametrization, and demographic data
title_sort reliably quantifying the evolving worldwide dynamic state of the covid-19 outbreak from death records, clinical parametrization, and demographic data
publisher Nature Publishing Group
series Scientific Reports
issn 2045-2322
publishDate 2021-10-01
description Abstract The dynamic characterization of the COVID-19 outbreak is critical to implement effective actions for its control and eradication but the information available at a global scale is not sufficiently reliable to be used directly. Here, we develop a quantitative approach to reliably quantify its temporal evolution and controllability through the integration of multiple data sources, including death records, clinical parametrization of the disease, and demographic data, and we explicitly apply it to countries worldwide, covering 97.4% of the human population, and to states within the United States (US). The validation of the approach shows that it can accurately reproduce the available prevalence data and that it can precisely infer the timing of nonpharmaceutical interventions. The results of the analysis identified general patterns of recession, stabilization, and resurgence. The diversity of dynamic behaviors of the outbreak across countries is paralleled by those of states and territories in the US, converging to remarkably similar global states in both cases. Our results offer precise insights into the dynamics of the outbreak and an efficient avenue for the estimation of the prevalence rates over time.
url https://doi.org/10.1038/s41598-021-99273-1
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