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An analysis of coronavirus disease 2019 with spline regression at province level during first-level response to major public health emergency out of Hubei, China

This study aims to locate the knots of cumulative coronavirus disease 2019 (COVID-19) case number during the first-level response to public health emergency in the provinces of China except Hubei. The provinces were grouped into three regions, namely eastern, central and western provinces, and the t...

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Autores principales: Liang, Chen, Shen, Li
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cambridge University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7809223/
https://www.ncbi.nlm.nih.gov/pubmed/33397520
http://dx.doi.org/10.1017/S095026882000312X
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author Liang, Chen
Shen, Li
author_facet Liang, Chen
Shen, Li
author_sort Liang, Chen
collection PubMed
description This study aims to locate the knots of cumulative coronavirus disease 2019 (COVID-19) case number during the first-level response to public health emergency in the provinces of China except Hubei. The provinces were grouped into three regions, namely eastern, central and western provinces, and the trends between adjacent knots were compared among the three regions. COVID-19 case number, migration scale index, Baidu index, demographic, economic and public health resource data were collected from 22 Chinese provinces from 19 January 2020 to 12 March 2020. Spline regression was applied to the data of all included, eastern, central and western provinces. The research period was divided into three stages by two knots. The first stage (from 19 January to around 25 January) was similar among three regions. However, in the second stage, growth of COVID-19 case number was flatter and lasted longer in western provinces (from 25 January to 18 February) than in eastern and central provinces (from 26 February to around 11 February). In the third stage, the growth of COVID-19 case number slowed down in all the three regions. Included covariates were different among the three regions. Overall, spline regression with covariates showed the different change patterns in eastern, central and western provinces, which provided a better insight into regional characteristics of COVID-19 pandemic.
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spelling pubmed-78092232021-01-15 An analysis of coronavirus disease 2019 with spline regression at province level during first-level response to major public health emergency out of Hubei, China Liang, Chen Shen, Li Epidemiol Infect Original Paper This study aims to locate the knots of cumulative coronavirus disease 2019 (COVID-19) case number during the first-level response to public health emergency in the provinces of China except Hubei. The provinces were grouped into three regions, namely eastern, central and western provinces, and the trends between adjacent knots were compared among the three regions. COVID-19 case number, migration scale index, Baidu index, demographic, economic and public health resource data were collected from 22 Chinese provinces from 19 January 2020 to 12 March 2020. Spline regression was applied to the data of all included, eastern, central and western provinces. The research period was divided into three stages by two knots. The first stage (from 19 January to around 25 January) was similar among three regions. However, in the second stage, growth of COVID-19 case number was flatter and lasted longer in western provinces (from 25 January to 18 February) than in eastern and central provinces (from 26 February to around 11 February). In the third stage, the growth of COVID-19 case number slowed down in all the three regions. Included covariates were different among the three regions. Overall, spline regression with covariates showed the different change patterns in eastern, central and western provinces, which provided a better insight into regional characteristics of COVID-19 pandemic. Cambridge University Press 2021-01-05 /pmc/articles/PMC7809223/ /pubmed/33397520 http://dx.doi.org/10.1017/S095026882000312X Text en © The Author(s) 2021 http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Paper
Liang, Chen
Shen, Li
An analysis of coronavirus disease 2019 with spline regression at province level during first-level response to major public health emergency out of Hubei, China
title An analysis of coronavirus disease 2019 with spline regression at province level during first-level response to major public health emergency out of Hubei, China
title_full An analysis of coronavirus disease 2019 with spline regression at province level during first-level response to major public health emergency out of Hubei, China
title_fullStr An analysis of coronavirus disease 2019 with spline regression at province level during first-level response to major public health emergency out of Hubei, China
title_full_unstemmed An analysis of coronavirus disease 2019 with spline regression at province level during first-level response to major public health emergency out of Hubei, China
title_short An analysis of coronavirus disease 2019 with spline regression at province level during first-level response to major public health emergency out of Hubei, China
title_sort analysis of coronavirus disease 2019 with spline regression at province level during first-level response to major public health emergency out of hubei, china
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7809223/
https://www.ncbi.nlm.nih.gov/pubmed/33397520
http://dx.doi.org/10.1017/S095026882000312X
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