A logistic model for age-specific COVID-19 case-fatality rates

To develop a mathematical model to characterize age-specific case-fatality rates (CFR) of COVID-19. Based on 2 large-scale Chinese and Italian CFR data, a logistic model was derived to provide quantitative insight on the dynamics between CFR and age. We inferred that CFR increased faster in Italy th...

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Detalles Bibliográficos
Autores principales: Gao, Xiang, Dong, Qunfeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Brief Communications
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7382619/
https://www.ncbi.nlm.nih.gov/pubmed/32734152
http://dx.doi.org/10.1093/jamiaopen/ooaa025
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author Gao, Xiang
Dong, Qunfeng
author_facet Gao, Xiang
Dong, Qunfeng
author_sort Gao, Xiang
collection PubMed
description To develop a mathematical model to characterize age-specific case-fatality rates (CFR) of COVID-19. Based on 2 large-scale Chinese and Italian CFR data, a logistic model was derived to provide quantitative insight on the dynamics between CFR and age. We inferred that CFR increased faster in Italy than in China, as well as in females over males. In addition, while CFR increased with age, the rate of growth eventually slowed down, with a predicted theoretical upper limit for males (32%), females (21%), and the general population (23%). Our logistic model provided quantitative insight on the dynamics of CFR.
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spelling pubmed-73826192020-07-29 A logistic model for age-specific COVID-19 case-fatality rates Gao, Xiang Dong, Qunfeng JAMIA Open Brief Communications To develop a mathematical model to characterize age-specific case-fatality rates (CFR) of COVID-19. Based on 2 large-scale Chinese and Italian CFR data, a logistic model was derived to provide quantitative insight on the dynamics between CFR and age. We inferred that CFR increased faster in Italy than in China, as well as in females over males. In addition, while CFR increased with age, the rate of growth eventually slowed down, with a predicted theoretical upper limit for males (32%), females (21%), and the general population (23%). Our logistic model provided quantitative insight on the dynamics of CFR. Oxford University Press 2020-04-13 /pmc/articles/PMC7382619/ /pubmed/32734152 http://dx.doi.org/10.1093/jamiaopen/ooaa025 Text en © The Author(s) 2020. Published by Oxford University Press on behalf of the American Medical Informatics Association. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Brief Communications
Gao, Xiang
Dong, Qunfeng
A logistic model for age-specific COVID-19 case-fatality rates
title A logistic model for age-specific COVID-19 case-fatality rates
title_full A logistic model for age-specific COVID-19 case-fatality rates
title_fullStr A logistic model for age-specific COVID-19 case-fatality rates
title_full_unstemmed A logistic model for age-specific COVID-19 case-fatality rates
title_short A logistic model for age-specific COVID-19 case-fatality rates
title_sort logistic model for age-specific covid-19 case-fatality rates
topic Brief Communications
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7382619/
https://www.ncbi.nlm.nih.gov/pubmed/32734152
http://dx.doi.org/10.1093/jamiaopen/ooaa025
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