Age-sex population adjusted analysis of disease severity in epidemics as a tool to devise public health policies for COVID-19

Abstract Governments continue to update social intervention strategies to contain COVID-19 infections. However, investigation of COVID-19 severity indicators across the population might help to design more precise strategies, balancing the need to keep people safe and to reduce the socio-economic bu...

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Autores principales: Carlo Vittorio Cannistraci, Maria Grazia Valsecchi, Ilaria Capua
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Lenguaje:EN
Publicado: Nature Portfolio 2021
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Acceso en línea:https://doaj.org/article/1a7a7787c9ad4aba8b140a3032592a6e
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spelling oai:doaj.org-article:1a7a7787c9ad4aba8b140a3032592a6e2021-12-02T15:57:21ZAge-sex population adjusted analysis of disease severity in epidemics as a tool to devise public health policies for COVID-1910.1038/s41598-021-89615-42045-2322https://doaj.org/article/1a7a7787c9ad4aba8b140a3032592a6e2021-06-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-89615-4https://doaj.org/toc/2045-2322Abstract Governments continue to update social intervention strategies to contain COVID-19 infections. However, investigation of COVID-19 severity indicators across the population might help to design more precise strategies, balancing the need to keep people safe and to reduce the socio-economic burden of generalized restriction precedures. Here, we propose a method for age-sex population-adjusted analysis of disease severity in epidemics that has the advantage to use simple and repeatable variables, which are daily or weekly available. This allows to monitor the effect of public health policies in short term, and to repeat these calculations over time to surveille epidemic dynamics and impact. Our method can help to define a risk-categorization of likeliness to develop a severe COVID-19 disease which requires intensive care or is indicative of a higher risk of dying. Indeed, analysis of suitable open-access COVID-19 data in three European countries indicates that individuals in the 0–40 age interval and females under 60 are significantly less likely to develop a severe condition and die, whereas males equal or above 60 are more likely at risk of severe disease and death. Hence, a combination of age-adaptive and sex-balanced guidelines for social interventions could represent key public health management tools for policymakers.Carlo Vittorio CannistraciMaria Grazia ValsecchiIlaria CapuaNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-8 (2021)
institution DOAJ
collection DOAJ
language EN
topic Medicine
R
Science
Q
spellingShingle Medicine
R
Science
Q
Carlo Vittorio Cannistraci
Maria Grazia Valsecchi
Ilaria Capua
Age-sex population adjusted analysis of disease severity in epidemics as a tool to devise public health policies for COVID-19
description Abstract Governments continue to update social intervention strategies to contain COVID-19 infections. However, investigation of COVID-19 severity indicators across the population might help to design more precise strategies, balancing the need to keep people safe and to reduce the socio-economic burden of generalized restriction precedures. Here, we propose a method for age-sex population-adjusted analysis of disease severity in epidemics that has the advantage to use simple and repeatable variables, which are daily or weekly available. This allows to monitor the effect of public health policies in short term, and to repeat these calculations over time to surveille epidemic dynamics and impact. Our method can help to define a risk-categorization of likeliness to develop a severe COVID-19 disease which requires intensive care or is indicative of a higher risk of dying. Indeed, analysis of suitable open-access COVID-19 data in three European countries indicates that individuals in the 0–40 age interval and females under 60 are significantly less likely to develop a severe condition and die, whereas males equal or above 60 are more likely at risk of severe disease and death. Hence, a combination of age-adaptive and sex-balanced guidelines for social interventions could represent key public health management tools for policymakers.
format article
author Carlo Vittorio Cannistraci
Maria Grazia Valsecchi
Ilaria Capua
author_facet Carlo Vittorio Cannistraci
Maria Grazia Valsecchi
Ilaria Capua
author_sort Carlo Vittorio Cannistraci
title Age-sex population adjusted analysis of disease severity in epidemics as a tool to devise public health policies for COVID-19
title_short Age-sex population adjusted analysis of disease severity in epidemics as a tool to devise public health policies for COVID-19
title_full Age-sex population adjusted analysis of disease severity in epidemics as a tool to devise public health policies for COVID-19
title_fullStr Age-sex population adjusted analysis of disease severity in epidemics as a tool to devise public health policies for COVID-19
title_full_unstemmed Age-sex population adjusted analysis of disease severity in epidemics as a tool to devise public health policies for COVID-19
title_sort age-sex population adjusted analysis of disease severity in epidemics as a tool to devise public health policies for covid-19
publisher Nature Portfolio
publishDate 2021
url https://doaj.org/article/1a7a7787c9ad4aba8b140a3032592a6e
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