Association between the New COVID-19 Cases and Air Pollution with Meteorological Elements in Nine Counties of New York State
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Otros documentos de la autoría: Díaz-Avalos, Carlos; Juan, Pablo; Chaudhuri, Somnath; Sáez, Marc; Serra, Laura
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Association between the New COVID-19 Cases and Air Pollution with Meteorological Elements in Nine Counties of New York StateFecha de publicación
2020-12-04Editor
MDPIISSN
1660-4601Cita bibliográfica
Díaz-Avalos, Carlos; Juan, Pablo; Chaudhuri, Somnath; Sáez, Marc; Serra, Laura. 2020. "Association between the New COVID-19 Cases and Air Pollution with Meteorological Elements in Nine Counties of New York State" Int. J. Environ. Res. Public Health 17, no. 23: 9055.Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
https://www.mdpi.com/1660-4601/17/23/9055Versión
info:eu-repo/semantics/publishedVersionResumen
The principal objective of this article is to assess the possible association between the number of COVID-19 infected cases and the concentrations of fine particulate matter (PM2.5) and ozone (O3), atmospheric pollutants ... [+]
The principal objective of this article is to assess the possible association between the number of COVID-19 infected cases and the concentrations of fine particulate matter (PM2.5) and ozone (O3), atmospheric pollutants related to people’s mobility in urban areas, taking also into account the effect of meteorological conditions. We fit a generalized linear mixed model which includes spatial and temporal terms in order to detect the effect of the meteorological elements and COVID-19 infected cases on the pollutant concentrations. We consider nine counties of the state of New York which registered the highest number of COVID-19 infected cases. We implemented a Bayesian method using integrated nested Laplace approximation (INLA) with a stochastic partial differential equation (SPDE). The results emphasize that all the components used in designing the model contribute to improving the predicted values and can be included in designing similar real-world data (RWD) models. We found only a weak association between PM2.5 and ozone concentrations with COVID-19 infected cases. Records of COVID-19 infected cases and other covariates data from March to May 2020 were collected from electronic health records (EHRs) and standard RWD sources. [-]
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Int. J. Environ. Res. Public Health 2020, 17, 9055Proyecto de investigación
PAPIIT-UNAM IG100221Derechos de acceso
© 2020 by the authors. Licensee MDPI, Basel, Switzerland.
info:eu-repo/semantics/openAccess
info:eu-repo/semantics/openAccess
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