Association between the New COVID-19 Cases and Air Pollution with Meteorological Elements in Nine Counties of New York State

Carlos Díaz-Avalos, Pablo Juan, Somnath Chaudhuri, Marc Sáez and Laura Serra
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Carlos Díaz-Avalos: Department of Probability and Statistics, IIMAS, Universidad Nacional Autónoma de México, Mexico City 04510, Mexico
Pablo Juan: Department of Mathematics and IMAC, Universitat Jaume I, Castellón, 12006 Castellón, Spain
Somnath Chaudhuri: Department of Mathematics, Universitat Jaume I, 12006 Castellón, Spain
Marc Sáez: Research Group on Statistics, Econometrics and Health (GRECS), University of Girona, 17003 Girona, Spain
Laura Serra: Research Group on Statistics, Econometrics and Health (GRECS), University of Girona, 17003 Girona, Spain

IJERPH, 2020, vol. 17, issue 23, 1-18

Abstract: 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 (PM 2.5 ) and ozone (O 3 ), 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 PM 2.5 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.

Keywords: COVID-19; INLA; RWD; PM 2.5; O 3; New York (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
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