About: Gaussian approach for probability and correlation between the number of COVID-19 cases and the air pollution in Lima

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About: Gaussian approach for probability and correlation between the number of COVID-19 cases and the air pollution in Lima Goto Sponge NotDistinct Permalink

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	Gaussian approach for probability and correlation between the number of COVID-19 cases and the air pollution in Lima
Creator	Arias Velásquez, Ricardo Lara, Mejía Vanessa, Jennifer
source	Medline; PMC
abstract	At the end of February 2020, Peru started the first cases of pneumonia associated with coronavirus (COVID-19), they were reported in Lima, Peru (Rodriguez-Morales et al., 2020). Therefore, the first week on March started with 72 infected people, the government published new law for a national crisis by COVID-19 pandemic (Vizcarra et al., 2020), with a quarantine in each city of Peru. Our analysis has considered March and April 2020, for air quality measurement and infections in Lima, the data collected on 6 meteorological stations with CO (carbon monoxide), NO(2) (nitrogen oxide), O(3) (ozone), SO(2) (sulfur dioxide), PM(10) and PM(2.5) (particle matter with diameter aerodynamic less than 2.5 and 10 m respectively). As a result, the average of these concentrations and the hospital information is recollected per hour. This analysis is executed during the quarantine an important correlation is discovered in the zone with highest infection by COVID-19, NO(2) and PM(10), even though in a reduction of air pollution in Lima. In this paper, we proposed a classification model by Reduced-Space Gaussian Process Regression for air pollution and infections; with technological and environmental dynamics and global change associated COVID-19. An evaluation of zones in Lima city, results have demonstrated influence of industrial influence in air pollution and infections by COVID-19 before and after quarantine during the last 28 days since the first infection in Peru; the problems relating to data management were validated with a successful classification and cluster analysis for future works in COVID-19 influence by environmental conditions.
has issue date	2020-07-03(xsd:dateTime)
bibo:doi	10.1016/j.uclim.2020.100664
bibo:pmid	32834964
has license	no-cc
sha1sum (hex)	73576635362767f5b8c3228287c93b0b16264af0
schema:url	https://doi.org/10.1016/j.uclim.2020.100664
resource representing a document's title	Gaussian approach for probability and correlation between the number of COVID-19 cases and the air pollution in Lima
has PubMed Central identifier	PMC7332952
has PubMed identifier	32834964
schema:publication	Urban Clim
resource representing a document's body	covid:73576635362767f5b8c3228287c93b0b16264af0#body_text
is schema:about of	named entity 'influence' named entity 'Peru' named entity 'COVID-19' named entity 'reduction' named entity 'linear combination' named entity 'NO2' named entity 'relating' named entity 'sulfur dioxide' named entity 'industrial' named entity 'executed' named entity '2002' named entity 'days' named entity 'del' named entity 'number' named entity 'Gaussian' named entity 'VECTOR' named entity 'OUR' named entity 'PROCESS' named entity '287' named entity 'PARA' named entity 'HAVE' named entity 'PROBLEMS' named entity 'PROPOSED' named entity 'DAYS' named entity 'DATA COLLECTED' named entity 'OUTPUT' named entity 'AIR QUALITY' named entity 'SO2' named entity 'COMBINATION' named entity 'LATER' named entity 'probability' named entity 'hospital' named entity 'process' named entity 'Journal' named entity 'del' named entity 'cases' named entity 'April' named entity 'published' named entity '2018' named entity 'avoided' named entity 'concentrations' named entity 'infections' named entity 'air pollution' named entity 'COVID-19' named entity 'layer' named entity 'correlation' named entity 'SO2' named entity 'environmental' named entity 'Lima' named entity 'PM10' named entity 'started' named entity 'quarantine' named entity 'Lima' named entity 'quarantine' named entity '28 days' named entity 'Lima' named entity 'Gaussian Process' named entity 'SO2' named entity 'NO2' named entity 'COVID-19' named entity 'quarantine' named entity 'COVID-19' named entity 'air pollution' named entity 'global change' named entity 'PM10' named entity 'probability' named entity 'probability' named entity 'Gaussian' named entity 'Lombardy' named entity 'Gaussian distribution' named entity 'air pollution' named entity 'NO2' named entity 'nonlinear' named entity 'air pollution' named entity 'particulate matter' named entity 'immunocompromised' named entity 'COVID-19' named entity 'Bayes rule' named entity 'PM2.5'

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