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Ambient air pollutants, meteorological factors and their interactions affect confirmed cases of COVID-19 in 120 Chinese cities
Jianli Zhou; Linyuan Qin; Nan Liu; Xiaojing Meng.
Afiliación
  • Jianli Zhou; Department of Occupational Health and Occupational Medicine, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern
  • Linyuan Qin; Department of Epidemiology and Statistics, School of Public Health, Guilin Medical University, Guilin, 541001, P. R. China.
  • Nan Liu; Department of Occupational Health and Occupational Medicine, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern
  • Xiaojing Meng; Department of Occupational Health and Occupational Medicine, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern
Preprint en Inglés | medRxiv | ID: ppmedrxiv-20111542
ABSTRACT
Emerging evidences have confirmed effects of meteorological factors on novel coronavirus disease 2019 (COVID-19). However, few studies verify the impact of air pollutants on this pandemic. This study aims to explore the association of ambient air pollutants, meteorological factors and their interactions effect confirmed case counts of COVID-19 in 120 Chinese cities. Here, we collected total confirmed cases of COVID-19 by combining with meteorological factors and air pollutants data from 15th January 2020 to 18th March 2020 in 120 Chinese cities. Spearman correlation analysis was employed to estimate the association between two variables; univariate and multivariate negative binomial regression analysis were applied to explore the effect of air pollutants and meteorological parameters on the COVID-19 confirmed cases. Positive associations were found between the confirmed cases of COVID-19 and carbon monoxide (CO), aerodynamic particulate matter with aerodynamic diameter [≤]2.5 m (PM2.5), relative humidity (RH) and air pressure (AP). And negative association was found for sulfur dioxide (SO2). In addition, multivariate negative binomial regression analysis suggested that confirmed cases of COVID-19 was positively correlated with ozone (O3) in lag 0 day while it was negatively associated with wind velocity (WV) in lag 14 days, and the pollutants-meteorological factors interactions also associate with COVID-19. In conclusions, air pollutants and meteorological factors and their interactions all associate with COVID-19.
Licencia
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Texto completo: Disponible Colección: Preprints Base de datos: medRxiv Idioma: Inglés Año: 2020 Tipo del documento: Preprint
Texto completo: Disponible Colección: Preprints Base de datos: medRxiv Idioma: Inglés Año: 2020 Tipo del documento: Preprint
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