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A New Analysis of Real-Time Fatality Rate in the Initial Stage of COVID-19

Mortality is one of the most important epidemiological measures and a key indicator of the effectiveness of potential treatments or interventions. In this paper, a permutation test method of variance analysis is proposed to test the null hypothesis that the real-time fatality rates of multiple group...

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Detalles Bibliográficos
Autores principales: Zhou, Chuanbo, Fang, Jiaohong, Mao, Mingzhi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10378078/
https://www.ncbi.nlm.nih.gov/pubmed/37509975
http://dx.doi.org/10.3390/e25071028
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author Zhou, Chuanbo
Fang, Jiaohong
Mao, Mingzhi
author_facet Zhou, Chuanbo
Fang, Jiaohong
Mao, Mingzhi
author_sort Zhou, Chuanbo
collection PubMed
description Mortality is one of the most important epidemiological measures and a key indicator of the effectiveness of potential treatments or interventions. In this paper, a permutation test method of variance analysis is proposed to test the null hypothesis that the real-time fatality rates of multiple groups were equal during the epidemic period. In light of large-scale simulation studies, the proposed test method can accurately identify the differences between different groups and display satisfactory performance. We apply the proposed method to the real dataset of the COVID-19 epidemic in mainland China (excluding Hubei), Hubei Province (excluding Wuhan), and Wuhan from 31 January 2020 to 30 March 2020. By comparing the differences in the disease severity for differential cities, we show that the severity of the early disease of COVID-19 may be related to the effectiveness of interventions and the improvement in medical resources.
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spelling pubmed-103780782023-07-29 A New Analysis of Real-Time Fatality Rate in the Initial Stage of COVID-19 Zhou, Chuanbo Fang, Jiaohong Mao, Mingzhi Entropy (Basel) Article Mortality is one of the most important epidemiological measures and a key indicator of the effectiveness of potential treatments or interventions. In this paper, a permutation test method of variance analysis is proposed to test the null hypothesis that the real-time fatality rates of multiple groups were equal during the epidemic period. In light of large-scale simulation studies, the proposed test method can accurately identify the differences between different groups and display satisfactory performance. We apply the proposed method to the real dataset of the COVID-19 epidemic in mainland China (excluding Hubei), Hubei Province (excluding Wuhan), and Wuhan from 31 January 2020 to 30 March 2020. By comparing the differences in the disease severity for differential cities, we show that the severity of the early disease of COVID-19 may be related to the effectiveness of interventions and the improvement in medical resources. MDPI 2023-07-06 /pmc/articles/PMC10378078/ /pubmed/37509975 http://dx.doi.org/10.3390/e25071028 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zhou, Chuanbo
Fang, Jiaohong
Mao, Mingzhi
A New Analysis of Real-Time Fatality Rate in the Initial Stage of COVID-19
title A New Analysis of Real-Time Fatality Rate in the Initial Stage of COVID-19
title_full A New Analysis of Real-Time Fatality Rate in the Initial Stage of COVID-19
title_fullStr A New Analysis of Real-Time Fatality Rate in the Initial Stage of COVID-19
title_full_unstemmed A New Analysis of Real-Time Fatality Rate in the Initial Stage of COVID-19
title_short A New Analysis of Real-Time Fatality Rate in the Initial Stage of COVID-19
title_sort new analysis of real-time fatality rate in the initial stage of covid-19
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10378078/
https://www.ncbi.nlm.nih.gov/pubmed/37509975
http://dx.doi.org/10.3390/e25071028
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