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?:abstract
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OBJECTIVE To examine the association between six air pollutants and COVID-19 infection in two clusters that accounted for 83% of total confirmed cases in South Korea. METHODS We collected the data on daily confirmed cases between February 24, 2020 and September 12, 2020. Data on six air pollutants (PM2.5 , PM10 , O3 , NO2 , CO, and SO2 ) and four meteorological factors (temperature, wind speed, humidity, and air pressure) were obtained on five days prior to the research period. generalized additive model and the distributed lag nonlinear model were applied to generate the odds ratios (ORs) and 95% confidence intervals (CIs) for the associations. Pooled estimates for clusters were obtained by applying a random-effects model. RESULTS We found that NO2 concentration was positively associated with daily confirmed cases in both Seoul-Gyeonggi and Daegu-Gyeongbuk clusters, with ORs (95% CIs) of 1.22 (1.03-1.44) and 1.66 (1.25-2.19), respectively. However, SO2 concentration was associated with daily confirmed cases in the Seoul-Gyeonggi cluster only (OR=1.30, 95% CI=1.10-1.54), whereas PM2.5 and CO concentrations were observed to be associated with daily confirmed cases in the Daegu-Gyeongbuk cluster only (OR=1.14, 95% CI=1.02-1.27 and OR=1.30, 95% CI=1.15-1.48, respectively). CONCLUSIONS In Seoul-Gyeonggi and Daegu-Gyeongbuk, the two main clusters of Covid-19 infection in South Korea, NO2 concentration was positively associated with daily confirmed cases. The effect of PM2.5 , CO, and SO2 on COVID-19 infection differed between the clusters.
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