About: Significance of geographical factors to the COVID-19 outbreak in India

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

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	Significance of geographical factors to the COVID-19 outbreak in India
Creator	Banerjee, Sreejita Das, Sumit Gupta, Amitesh
source	Medline; PMC
abstract	Recently, the large outbreak of COVID-19 cases all over the world has whacked India with about 30,000 confirmed cases within the first 3 months of transmission. The present study used long-term climatic records of air temperature (T), rainfall (R), actual evapotranspiration (AET), solar radiation (SR), specific humidity (SH), wind speed (WS) with topographic altitude (E) and population density (PD) at the regional level to investigate the spatial association with the number of COVID-19 infections (NI). Bivariate analysis failed to find any significant relation (except SR) with the number of infected cases within 36 provinces in India. Variable Importance of Projection (VIP) through Partial Least Square (PLS) technique signified higher importance of SR, T, R and AET. However, generalized additive model fitted with the log-transformed value of input variables and applying spline smoothening to PD and E, significantly found high accuracy of prediction (R(2) = 0.89), and thus well-explained complex heterogeneity among the association of regional parameters with COVID-19 cases in India. Our study suggests that comparatively hot and dry regions in lower altitude of the Indian territory are more prone to the infection by COVID-19 transmission. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s40808-020-00838-2) contains supplementary material, which is available to authorized users.
has issue date	2020-06-17(xsd:dateTime)
bibo:doi	10.1007/s40808-020-00838-2
bibo:pmid	32838021
has license	no-cc
sha1sum (hex)	a8c8bd9ec9fedb06c261d308c79c94f0c004cc53
schema:url	https://doi.org/10.1007/s40808-020-00838-2
resource representing a document's title	Significance of geographical factors to the COVID-19 outbreak in India
has PubMed Central identifier	PMC7299143
has PubMed identifier	32838021
schema:publication	Model Earth Syst Environ
resource representing a document's body	covid:a8c8bd9ec9fedb06c261d308c79c94f0c004cc53#body_text
is schema:about of	named entity 'Variable' named entity 'Projection' named entity 'records' covid:arg/a8c8bd9ec9fedb06c261d308c79c94f0c004cc53 named entity 'generalized additive model' named entity 'high' named entity 'VIP' named entity 'COVID-19' named entity 'air temperature' named entity 'However' named entity 'higher' named entity 'regional' named entity 'altitude' named entity 'PLS' named entity 'climatic' named entity 'population density' named entity 'solar radiation' named entity 'India' named entity 'COVID-19' named entity 'India' named entity 'evapotranspiration' named entity 'Wuhan' named entity 'topography' named entity 'COVID' named entity 'altitude' named entity 'long-term' named entity 'India' named entity 'COVID-19 cases' named entity 'virus' named entity 'April 27' named entity 'arid areas' named entity 'respiratory disorder' named entity 'climatic' named entity 'positive correlation' named entity 'China' named entity 'Wuhan' named entity 'spline function' named entity 'COVID' named entity 'transmissible disease' named entity 'COVID' named entity 'India' named entity 'correlation' named entity 'scientific investigations' named entity 'mainland of China' named entity 'Social distancing' named entity 'aridity index' named entity 'COVID-19' named entity 'follow-up' named entity 'SRTM' named entity 'vaccine' named entity 'India' named entity 'climatic' named entity 'India' named entity 'transmission rate' named entity 'geographical distribution' named entity 'long-term' named entity 'India' named entity 'topographic elevation' named entity 'Maharashtra' named entity 'air temperature' named entity 'tropical countries' named entity 'COVID-19 infection' named entity 'COVID' named entity 'Virus transmission' named entity 'mid-latitude' named entity 'COVID-19' named entity 'India' named entity 'meteorology' named entity 'India' named entity 'significance level' named entity 'meteorology' named entity 'climatic' named entity 'rank correlation' named entity 'mortality rate' named entity 'Hubei Province, China' named entity 'climatic' named entity 'COVID-19 cases' named entity 'long-term' named entity 'correlation'

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