Spatio-temporal distribution characteristics and influencing factors of COVID-19 in China

Abstract In December 2019, corona virus disease 2019 (COVID-19) has broken out in China. Understanding the distribution of disease at the national level contributes to the formulation of public health policies. There are several studies that investigating the influencing factors on distribution of C...

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Autores principales:	Youliang Chen, Qun Li, Hamed Karimian, Xunjun Chen, Xiaoming Li
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/fddd8813d14b451dbe611957ff1f81e4
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spelling	oai:doaj.org-article:fddd8813d14b451dbe611957ff1f81e42021-12-02T14:11:31ZSpatio-temporal distribution characteristics and influencing factors of COVID-19 in China10.1038/s41598-021-83166-42045-2322https://doaj.org/article/fddd8813d14b451dbe611957ff1f81e42021-02-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-83166-4https://doaj.org/toc/2045-2322Abstract In December 2019, corona virus disease 2019 (COVID-19) has broken out in China. Understanding the distribution of disease at the national level contributes to the formulation of public health policies. There are several studies that investigating the influencing factors on distribution of COVID-19 in China. However, more influencing factors need to be considered to improve our understanding about the current epidemic. Moreover, in the absence of effective medicine or vaccine, the Chinese government introduced a series of non-pharmaceutical interventions (NPIs). However, assessing and predicting the effectiveness of these interventions requires further study. In this paper, we used statistical techniques, correlation analysis and GIS mapping expression method to analyze the spatial and temporal distribution characteristics and the influencing factors of the COVID-19 in mainland China. The results showed that the spread of outbreaks in China’s non-Hubei provinces can be divided into five stages. Stage I is the initial phase of the COVID-19 outbreak; in stage II the new peak of the epidemic was observed; in stage III the outbreak was contained and new cases decreased; there was a rebound in stage IV, and stage V led to level off. Moreover, the cumulative confirmed cases were mainly concentrated in the southeastern part of China, and the epidemic in the cities with large population flows from Wuhan was more serious. In addition, statistically significant correlations were found between the prevalence of the epidemic and the temperature, rainfall and relative humidity. To evaluate the NPIs, we simulated the prevalence of the COVID-19 based on an improved SIR model and under different prevention intensity. It was found that our simulation results were compatible with the observed values and the parameter of the time function in the improved SIR model for China is a = − 0.0058. The findings and methods of this study can be effective for predicting and managing the epidemics and can be used as an aid for decision makers to control the current and future epidemics.Youliang ChenQun LiHamed KarimianXunjun ChenXiaoming LiNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Youliang Chen Qun Li Hamed Karimian Xunjun Chen Xiaoming Li Spatio-temporal distribution characteristics and influencing factors of COVID-19 in China
description	Abstract In December 2019, corona virus disease 2019 (COVID-19) has broken out in China. Understanding the distribution of disease at the national level contributes to the formulation of public health policies. There are several studies that investigating the influencing factors on distribution of COVID-19 in China. However, more influencing factors need to be considered to improve our understanding about the current epidemic. Moreover, in the absence of effective medicine or vaccine, the Chinese government introduced a series of non-pharmaceutical interventions (NPIs). However, assessing and predicting the effectiveness of these interventions requires further study. In this paper, we used statistical techniques, correlation analysis and GIS mapping expression method to analyze the spatial and temporal distribution characteristics and the influencing factors of the COVID-19 in mainland China. The results showed that the spread of outbreaks in China’s non-Hubei provinces can be divided into five stages. Stage I is the initial phase of the COVID-19 outbreak; in stage II the new peak of the epidemic was observed; in stage III the outbreak was contained and new cases decreased; there was a rebound in stage IV, and stage V led to level off. Moreover, the cumulative confirmed cases were mainly concentrated in the southeastern part of China, and the epidemic in the cities with large population flows from Wuhan was more serious. In addition, statistically significant correlations were found between the prevalence of the epidemic and the temperature, rainfall and relative humidity. To evaluate the NPIs, we simulated the prevalence of the COVID-19 based on an improved SIR model and under different prevention intensity. It was found that our simulation results were compatible with the observed values and the parameter of the time function in the improved SIR model for China is a = − 0.0058. The findings and methods of this study can be effective for predicting and managing the epidemics and can be used as an aid for decision makers to control the current and future epidemics.
format	article
author	Youliang Chen Qun Li Hamed Karimian Xunjun Chen Xiaoming Li
author_facet	Youliang Chen Qun Li Hamed Karimian Xunjun Chen Xiaoming Li
author_sort	Youliang Chen
title	Spatio-temporal distribution characteristics and influencing factors of COVID-19 in China
title_short	Spatio-temporal distribution characteristics and influencing factors of COVID-19 in China
title_full	Spatio-temporal distribution characteristics and influencing factors of COVID-19 in China
title_fullStr	Spatio-temporal distribution characteristics and influencing factors of COVID-19 in China
title_full_unstemmed	Spatio-temporal distribution characteristics and influencing factors of COVID-19 in China
title_sort	spatio-temporal distribution characteristics and influencing factors of covid-19 in china
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/fddd8813d14b451dbe611957ff1f81e4
work_keys_str_mv	AT youliangchen spatiotemporaldistributioncharacteristicsandinfluencingfactorsofcovid19inchina AT qunli spatiotemporaldistributioncharacteristicsandinfluencingfactorsofcovid19inchina AT hamedkarimian spatiotemporaldistributioncharacteristicsandinfluencingfactorsofcovid19inchina AT xunjunchen spatiotemporaldistributioncharacteristicsandinfluencingfactorsofcovid19inchina AT xiaomingli spatiotemporaldistributioncharacteristicsandinfluencingfactorsofcovid19inchina
_version_	1718391882680107008

Spatio-temporal distribution characteristics and influencing factors of COVID-19 in China

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