Short‐term exposure to ambient air pollution in association with COVID‐19 of two clusters in South Korea
Tung Hoang, Trung Quang Nguyen, Tho Thi Anh Tran
Abstract
Abstract Objectives This study aimed to examine the association between six air pollutants and COVID‐19 infection in two main clusters, which accounted for 83% of total confirmed cases in Korea. Methods We collected the data on daily confirmed cases between February 24, 2020 and September 12, 2020. Data on six air pollutants (PM 2.5 , PM 10 , O 3 , NO 2 , CO and SO 2 ) and four meteorological factors (temperature, wind speed, humidity and air pressure) were obtained on seven days prior to the research period. The generalised additive model and the distributed lag nonlinear model were applied to generate the relative risks (RRs) and 95% confidence intervals (CIs) for the associations. Pooled estimates for clusters were obtained by applying a random‐effects model. Results We found that NO 2 concentration was positively associated with daily confirmed cases in both Seoul‐Gyeonggi and Daegu‐Gyeongbuk clusters, with RRs (95% CIs) of 1.22 (1.03–1.44) and 1.66 (1.25–2.19), respectively. However, SO 2 concentration was observed to be associated with daily confirmed cases in the Seoul‐Gyeonggi cluster only (RR = 1.30, 95% CI = 1.10–1.54), whereas PM 2.5 and CO concentrations were observed to be associated with daily confirmed cases in the Daegu‐Gyeongbuk cluster only (RR = 1.14, 95% CI = 1.02–1.27 and RR = 1.30, 95% CI = 1.15–1.48, respectively). Conclusions Our data found that NO 2 concentration was positively associated with daily confirmed cases in both clusters, whereas the effect of PM 2.5 , CO and SO 2 on COVID‐19 infection in two clusters was different.