Research on the Spatial Correlation and Spatial Lag of COVID-19 Infection Based on Spatial Analysis

COVID-19 has spread throughout the world since the virus was discovered in 2019. Thus, this study aimed to identify the global transmission trend of the COVID-19 from the perspective of the spatial correlation and spatial lag. The research used primary data collected of daily increases in the amount...

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Autores principales:	Keqiang Dong, Liao Guo
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	COVID-19 spatial autocorrelation spatial lag model spatial Durbin model Environmental effects of industries and plants TD194-195 Renewable energy sources TJ807-830 Environmental sciences GE1-350
Acceso en línea:	https://doaj.org/article/b7f93761bb334fd4a3e5a4bbcf7339a8
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id	oai:doaj.org-article:b7f93761bb334fd4a3e5a4bbcf7339a8
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spelling	oai:doaj.org-article:b7f93761bb334fd4a3e5a4bbcf7339a82021-11-11T19:40:36ZResearch on the Spatial Correlation and Spatial Lag of COVID-19 Infection Based on Spatial Analysis10.3390/su1321120132071-1050https://doaj.org/article/b7f93761bb334fd4a3e5a4bbcf7339a82021-10-01T00:00:00Zhttps://www.mdpi.com/2071-1050/13/21/12013https://doaj.org/toc/2071-1050COVID-19 has spread throughout the world since the virus was discovered in 2019. Thus, this study aimed to identify the global transmission trend of the COVID-19 from the perspective of the spatial correlation and spatial lag. The research used primary data collected of daily increases in the amount of COVID-19 in 14 countries, confirmed diagnosis, recovered numbers, and deaths. Findings of the Moran index showed that the propagation of infection was aggregated between 9 May and 21 May based on the composite spatial weight matrix. The results from the Lagrange multiplier test indicated the COVID-19 patients can infect others with a lag.Keqiang DongLiao GuoMDPI AGarticleCOVID-19spatial autocorrelationspatial lag modelspatial Durbin modelEnvironmental effects of industries and plantsTD194-195Renewable energy sourcesTJ807-830Environmental sciencesGE1-350ENSustainability, Vol 13, Iss 12013, p 12013 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	COVID-19 spatial autocorrelation spatial lag model spatial Durbin model Environmental effects of industries and plants TD194-195 Renewable energy sources TJ807-830 Environmental sciences GE1-350
spellingShingle	COVID-19 spatial autocorrelation spatial lag model spatial Durbin model Environmental effects of industries and plants TD194-195 Renewable energy sources TJ807-830 Environmental sciences GE1-350 Keqiang Dong Liao Guo Research on the Spatial Correlation and Spatial Lag of COVID-19 Infection Based on Spatial Analysis
description	COVID-19 has spread throughout the world since the virus was discovered in 2019. Thus, this study aimed to identify the global transmission trend of the COVID-19 from the perspective of the spatial correlation and spatial lag. The research used primary data collected of daily increases in the amount of COVID-19 in 14 countries, confirmed diagnosis, recovered numbers, and deaths. Findings of the Moran index showed that the propagation of infection was aggregated between 9 May and 21 May based on the composite spatial weight matrix. The results from the Lagrange multiplier test indicated the COVID-19 patients can infect others with a lag.
format	article
author	Keqiang Dong Liao Guo
author_facet	Keqiang Dong Liao Guo
author_sort	Keqiang Dong
title	Research on the Spatial Correlation and Spatial Lag of COVID-19 Infection Based on Spatial Analysis
title_short	Research on the Spatial Correlation and Spatial Lag of COVID-19 Infection Based on Spatial Analysis
title_full	Research on the Spatial Correlation and Spatial Lag of COVID-19 Infection Based on Spatial Analysis
title_fullStr	Research on the Spatial Correlation and Spatial Lag of COVID-19 Infection Based on Spatial Analysis
title_full_unstemmed	Research on the Spatial Correlation and Spatial Lag of COVID-19 Infection Based on Spatial Analysis
title_sort	research on the spatial correlation and spatial lag of covid-19 infection based on spatial analysis
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/b7f93761bb334fd4a3e5a4bbcf7339a8
work_keys_str_mv	AT keqiangdong researchonthespatialcorrelationandspatiallagofcovid19infectionbasedonspatialanalysis AT liaoguo researchonthespatialcorrelationandspatiallagofcovid19infectionbasedonspatialanalysis
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Research on the Spatial Correlation and Spatial Lag of COVID-19 Infection Based on Spatial Analysis

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