Population response to air pollution and the risk of coronavirus disease in chinese cities during the early pandemic period

Abstract

Health behavior is a critical measure in controlling the coronavirus disease 2019 (COVID‐ 19) pandemic. We estimated the effect of health behaviors against air pollution on reducing the risk of COVID‐19 during the initial phase of the pandemic. The attack rates of COVID‐19 in 159 mainland Chinese cities during the first 2 weeks after the closure of major cities was estimated; air pollution level as a surrogate indicator of the mask‐wearing rate. Data on air pollution levels and meteorologic factors 2 weeks prior to the closure were obtained. The attack rate was compared with the level of air pollution using a generalized linear model after adjusting for confounders. When fine particulates (PM2.5) and nitrogen dioxide (NO2) levels increased by one unit of air quality index (AQI), the infection risk decreased by 0.7% and 3.4%, respectively. When PM2.5 levels exceeded 150 (level 4), the infection risk decreased (relative risk, RR = 0.635, 95% confidence interval, CI: 0.442 to 0.912 for level 4; RR = 0.529, 95% CI: 0.337 to 0.830 for level 5; respectively). After controlling for the number of high-speed railway routes, when PM2.5 and NO2 levels increased by one AQI, relative risk for PM2.5 and NO2 was 0.990 (95% CI, 0.984 to 0.997) and 0.946 (95% CI, 0.911 to 0.982), respectively, demonstrating a consistently negative association. It is postulated that, during the early phase of the pandemic, the cities with higher air pollution levels may represent the higher practice of mask‐wearing to protect from air pollution, which could have acted as a barrier to the transmission of the virus. This study highlights the importance of health behaviors, including mask‐wearing for preventing infections.