About: Spatial and temporal differentiation of COVID-19 epidemic spread in mainland China and its influencing factors

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: Spatial and temporal differentiation of COVID-19 epidemic spread in mainland China and its influencing factors Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Spatial and temporal differentiation of COVID-19 epidemic spread in mainland China and its influencing factors
Creator	Li, Yang Shen, Wei Liu, Shirui Qin, Yaochen Xie, Zhixiang Zheng, Zhicheng
Source	Elsevier; Medline; PMC
abstract	Abstract This paper uses the exploratory spatial data analysis and the geodetector method to analyze the spatial and temporal differentiation characteristics and the influencing factors of the COVID-19 (corona virus disease 2019) epidemic spread in mainland China based on the cumulative confirmed cases, average temperature, and socio-economic data. The results show that: (1) the epidemic spread rapidly from January 24 to February 20, 2020, and the distribution of the epidemic areas tended to be stable over time. The epidemic spread rate in Hubei province, in its surrounding, and in some economically developed cities was higher, while that in western part of China and in remote areas of central and eastern China was lower. (2) The global and local spatial correlation characteristics of the epidemic distribution present a positive correlation. Specifically, the global spatial correlation characteristics experienced a change process from agglomeration to decentralization. The local spatial correlation characteristics were mainly composed of the‘high-high’ and ‘low-low’ clustering types, and the situation of the contiguous layout was very significant. (3) The population inflow from Wuhan and the strength of economic connection were the main factors affecting the epidemic spread, together with the population distribution, transport accessibility, average temperature, and medical facilities, which affected the epidemic spread to varying degrees. (4) The detection factors interacted mainly through the mutual enhancement and nonlinear enhancement, and their influence on the epidemic spread rate exceeded that of single factors. Besides, each detection factor has an interval range that is conducive to the epidemic spread.
has issue date	2020-07-14(xsd:dateTime)
bibo:doi	10.1016/j.scitotenv.2020.140929
bibo:pmid	32687995
has license	els-covid
sha1sum (hex)	e23003d7525da0ebc4a5dbd59afbf51816a98948
schema:url	https://doi.org/10.1016/j.scitotenv.2020.140929
resource representing a document's title	Spatial and temporal differentiation of COVID-19 epidemic spread in mainland China and its influencing factors
has PubMed Central identifier	PMC7358148
has PubMed identifier	32687995
schema:publication	Sci Total Environ
resource representing a document's body	covid:e23003d7525da0ebc4a5dbd59afbf51816a98948#body_text
is schema:about of	named entity 'agglomeration' named entity 'mainland China' named entity 'types' named entity 'factors' named entity 'mutual' named entity 'Abstract' named entity 'corona virus' named entity 'The' named entity 'stable' named entity 'based' named entity 'spatial' named entity 'Journal' named entity 'LOWER' named entity '283' named entity 'VIRUS DISEASE' named entity 'DISTRIBUTION' named entity 'JANUARY' named entity 'CHARACTERISTICS' covid:arg/e23003d7525da0ebc4a5dbd59afbf51816a98948 named entity 'medical facilities' named entity 'temporal' named entity 'cumulative' named entity 'areas' named entity 'interacted' named entity 'influence' named entity 'epidemic' named entity 'Spatial' named entity 'interval' named entity 'clustering' named entity 'decentralization' named entity 'data' named entity 'population' named entity 'influencing' named entity 'Hubei' named entity 'mainland China' named entity 'epidemic spread' named entity 'Wuhan' named entity 'epidemic spread' named entity 'spatial correlation' named entity 'decentralization' named entity 'epidemic spread' named entity 'China' named entity 'spatial correlation' named entity 'China' named entity 'spatial data analysis' named entity 'mainland China' named entity 'COVID' named entity 'epidemic' named entity 'epidemic' named entity 'influencing' named entity 'Ezhou' named entity 'March 2' named entity 'nonlinear' named entity 'Wuhan' named entity 'COVID' named entity '8 days' named entity 'Wuhan' named entity 'LISA' named entity 'evolution' named entity 'significance level' named entity 'Wuhan' named entity 'virus' named entity 'heterogeneity' named entity 'Shaanxi' named entity 'Qianjiang' named entity 'Suizhou' named entity 'Tibet' named entity 'Gansu' named entity 'COVID' named entity 'COVID' named entity 'spatial distribution' named entity 'prevention and control' named entity 'epidemic spread' named entity 'epidemic spread' named entity 'Qianjiang' named entity 'COVID'

Faceted Search & Find service v1.13.91 as of Mar 24 2020

Alternative Linked Data Documents: Sponger | ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 07.20.3229 as of Jul 10 2020, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (94 GB total memory)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software