Association between short-term exposure to air pollution and COVID-19 infection: Evidence from China

https://doi.org/10.1016/j.scitotenv.2020.138704Get rights and content

Highlights

  • There was a significant relationship between air pollution and COVID-19 infection after controlling for confounding factors.

  • Positive associations of PM2.5, PM10, CO, NO2 and O3 with COVID-19 confirmed cases were observed.

  • However, SO2 was negatively associated with the number of daily COVID-19 confirmed cases.

Abstract

The novel coronavirus pneumonia, namely COVID-19, has become a global public health problem. Previous studies have found that air pollution is a risk factor for respiratory infection by carrying microorganisms and affecting body's immunity. This study aimed to explore the relationship between ambient air pollutants and the infection caused by the novel coronavirus. Daily confirmed cases, air pollution concentration and meteorological variables in 120 cities were obtained from January 23, 2020 to February 29, 2020 in China. We applied a generalized additive model to investigate the associations of six air pollutants (PM2.5, PM10, SO2, CO, NO2 and O3) with COVID-19 confirmed cases. We observed significantly positive associations of PM2.5, PM10, NO2 and O3 in the last two weeks with newly COVID-19 confirmed cases. A 10-μg/m3 increase (lag0–14) in PM2.5, PM10, NO2, and O3 was associated with a 2.24% (95% CI: 1.02 to 3.46), 1.76% (95% CI: 0.89 to 2.63), 6.94% (95% CI: 2.38 to 11.51), and 4.76% (95% CI: 1.99 to 7.52) increase in the daily counts of confirmed cases, respectively. However, a 10-μg/m3 increase (lag0–14) in SO2 was associated with a 7.79% decrease (95% CI: −14.57 to −1.01) in COVID-19 confirmed cases. Our results indicate that there is a significant relationship between air pollution and COVID-19 infection, which could partially explain the effect of national lockdown and provide implications for the control and prevention of this novel disease.

Keywords

Air pollution
Novel coronavirus pneumonia
COVID-19
Generalized additive model

Cited by (0)

View Abstract