Predictability of COVID-19-related morbidity and mortality based on model estimations to establish proactive protocols of countermeasures

Abstract The COVID-19 pandemic (SARS-CoV-2) has revealed the need for proactive protocols to react and act, imposing preventive and restrictive countermeasures on time in any society. The extent to which confirmed cases can predict the morbidity and mortality in a society remains an unresolved issue...

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Autores principales:	Göran Svensson, Rocio Rodriguez, Carmen Padin
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/a831c319ad684d46aa39759f60f1bdf9
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spelling	oai:doaj.org-article:a831c319ad684d46aa39759f60f1bdf92021-12-02T16:08:07ZPredictability of COVID-19-related morbidity and mortality based on model estimations to establish proactive protocols of countermeasures10.1038/s41598-021-93932-z2045-2322https://doaj.org/article/a831c319ad684d46aa39759f60f1bdf92021-07-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-93932-zhttps://doaj.org/toc/2045-2322Abstract The COVID-19 pandemic (SARS-CoV-2) has revealed the need for proactive protocols to react and act, imposing preventive and restrictive countermeasures on time in any society. The extent to which confirmed cases can predict the morbidity and mortality in a society remains an unresolved issue. The research objective is therefore to test a generic model’s predictability through time, based on percentage of confirmed cases on hospitalized patients, ICU patients and deceased. This study reports the explanatory and predictive ability of COVID-19-related healthcare data, such as whether there is a spread of a contagious and virulent virus in a society, and if so, whether the morbidity and mortality can be estimated in advance in the population. The model estimations stress the implementation of a pandemic strategy containing a proactive protocol entailing what, when, where, who and how countermeasures should be in place when a virulent virus (e.g. SARS-CoV-1, SARS-CoV-2 and MERS) or pandemic strikes next time. Several lessons for the future can be learnt from the reported model estimations. One lesson is that COVID-19-related morbidity and mortality in a population is indeed predictable. Another lesson is to have a proactive protocol of countermeasures in place.Göran SvenssonRocio RodriguezCarmen PadinNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-10 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Göran Svensson Rocio Rodriguez Carmen Padin Predictability of COVID-19-related morbidity and mortality based on model estimations to establish proactive protocols of countermeasures
description	Abstract The COVID-19 pandemic (SARS-CoV-2) has revealed the need for proactive protocols to react and act, imposing preventive and restrictive countermeasures on time in any society. The extent to which confirmed cases can predict the morbidity and mortality in a society remains an unresolved issue. The research objective is therefore to test a generic model’s predictability through time, based on percentage of confirmed cases on hospitalized patients, ICU patients and deceased. This study reports the explanatory and predictive ability of COVID-19-related healthcare data, such as whether there is a spread of a contagious and virulent virus in a society, and if so, whether the morbidity and mortality can be estimated in advance in the population. The model estimations stress the implementation of a pandemic strategy containing a proactive protocol entailing what, when, where, who and how countermeasures should be in place when a virulent virus (e.g. SARS-CoV-1, SARS-CoV-2 and MERS) or pandemic strikes next time. Several lessons for the future can be learnt from the reported model estimations. One lesson is that COVID-19-related morbidity and mortality in a population is indeed predictable. Another lesson is to have a proactive protocol of countermeasures in place.
format	article
author	Göran Svensson Rocio Rodriguez Carmen Padin
author_facet	Göran Svensson Rocio Rodriguez Carmen Padin
author_sort	Göran Svensson
title	Predictability of COVID-19-related morbidity and mortality based on model estimations to establish proactive protocols of countermeasures
title_short	Predictability of COVID-19-related morbidity and mortality based on model estimations to establish proactive protocols of countermeasures
title_full	Predictability of COVID-19-related morbidity and mortality based on model estimations to establish proactive protocols of countermeasures
title_fullStr	Predictability of COVID-19-related morbidity and mortality based on model estimations to establish proactive protocols of countermeasures
title_full_unstemmed	Predictability of COVID-19-related morbidity and mortality based on model estimations to establish proactive protocols of countermeasures
title_sort	predictability of covid-19-related morbidity and mortality based on model estimations to establish proactive protocols of countermeasures
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/a831c319ad684d46aa39759f60f1bdf9
work_keys_str_mv	AT goransvensson predictabilityofcovid19relatedmorbidityandmortalitybasedonmodelestimationstoestablishproactiveprotocolsofcountermeasures AT rociorodriguez predictabilityofcovid19relatedmorbidityandmortalitybasedonmodelestimationstoestablishproactiveprotocolsofcountermeasures AT carmenpadin predictabilityofcovid19relatedmorbidityandmortalitybasedonmodelestimationstoestablishproactiveprotocolsofcountermeasures
_version_	1718384615130923008

Predictability of COVID-19-related morbidity and mortality based on model estimations to establish proactive protocols of countermeasures

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