Abstract
OBJECTIVE: To determine whether ambient air pollutants and meteorological variables are associated with daily COVID-19 incidence. DESIGN: A retrospective cohort from January 25 to February 29, 2020. SETTING: Cities of Wuhan, Xiaogan, and Huanggang, China. PATIENTS: The COVID-19 cases detected each day. METHODS: We collected daily data of COVID-19 incidence, 8 ambient air pollutants (particulate matter of ≤2.5 µm [PM2.5], particulate matter ≤10 µm [PM10], sulfur dioxide [SO2], carbon monoxide [CO], nitrogen dioxide [NO2], and maximum 8-h moving average concentrations for ozone [O3-8h]) and 3 meteorological variables (temperature, relative humidity, and wind) in China's 3 worst COVID-19-stricken cities during the study period. The multivariate Poisson regression was performed to understand their correlation. RESULTS: Daily COVID-19 incidence was positively associated with PM2.5 and humidity in all cities. Specifically, the relative risk (RR) of PM2.5 for daily COVID-19 incidences were 1.036 (95% confidence interval [CI], 1.032-1.039) in Wuhan, 1.059 (95% CI, 1.046-1.072) in Xiaogan, and 1.144 (95% CI, 1.12-1.169) in Huanggang. The RR of humidity for daily COVID-19 incidence was consistently lower than that of PM2.5, and this difference ranged from 0.027 to 0.111. Moreover, PM10 and temperature also exhibited a notable correlation with daily COVID-19 incidence, but in a negative pattern The RR of PM10 for daily COVID-19 incidence ranged from 0.915 (95% CI, 0.896-0.934) to 0.961 (95% CI, 0.95-0.972, while that of temperature ranged from 0.738 (95% CI, 0.717-0.759) to 0.969 (95% CI, 0.966-0.973). CONCLUSIONS: Our data show that PM2.5 and humidity are substantially associated with an increased risk of COVID-19 and that PM10 and temperature are substantially associated with a decreased risk of COVID-19.