COVID-19 has become a pandemic. The influence of meteorological factors on the transmission and spread of COVID-19 is of interest. This study sought to examine the associations of daily average temperature (AT) and relative humidity (ARH) with the daily counts of COVID-19 cases in 30 Chinese provinces (in Hubei from December 1, 2019 to February 11, 2020 and in other provinces from January 20, 2020 to Februarys 11, 2020). A Generalized Additive Model (GAM) was fitted to quantify the province-specific associations between meteorological variables and the daily cases of COVID-19 during the study periods. In the model, the 14-day exponential moving averages (EMAs) of AT and ARH, and their interaction were included with time trend and health-seeking behavior adjusted. Their spatial distributions were visualized. AT and ARH showed significantly negative associations with COVID-19 with a significant interaction between them (0.04, 95% confidence interval: 0.004–0.07) in Hubei. Every 1 °C increase in the AT led to a decrease in the daily confirmed cases by 36% to 57% when ARH was in the range from 67% to 85.5%. Every 1% increase in ARH led to a decrease in the daily confirmed cases by 11% to 22% when AT was in the range from 5.04 °C to 8.2 °C. However, these associations were not consistent throughout Mainland China.

Additional Metadata
Keywords China, COVID-19, Meteorological factors, Time-series analysis
Persistent URL dx.doi.org/10.1016/j.scitotenv.2020.138778, hdl.handle.net/1765/126359
Journal Science of the Total Environment
Citation
Qi, H. (Hongchao), Xiao, S. (Shuang), Shi, R. (Runye), Ward, M.P. (Michael P.), Chen, Y. (Yue), Tu, W. (Wei), … Zhang, Z. (Zhijie). (2020). COVID-19 transmission in Mainland China is associated with temperature and humidity: A time-series analysis. Science of the Total Environment, 728. doi:10.1016/j.scitotenv.2020.138778