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. 2020 Aug 1:728:138778.
doi: 10.1016/j.scitotenv.2020.138778. Epub 2020 Apr 19.

COVID-19 transmission in Mainland China is associated with temperature and humidity: A time-series analysis

Hongchao Qi  1 , Shuang Xiao  2 , Runye Shi  2 , Michael P Ward  3 , Yue Chen  4 , Wei Tu  5 , Qing Su  2 , Wenge Wang  2 , Xinyi Wang  2 , Zhijie Zhang  6
Affiliations

COVID-19 transmission in Mainland China is associated with temperature and humidity: A time-series analysis

Hongchao Qi et al. Sci Total Environ. .

Abstract

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.

Keywords: COVID-19; China; Meteorological factors; Time-series analysis.

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Conflict of interest statement

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Unlabelled Image
Graphical abstract
Fig. 1
Fig. 1
The distribution of (a) cumulative confirmed cases, (b) average AT, and (c) average ARH in all provinces surveyed in China.
Fig. 2
Fig. 2
The time series of the daily counts, daily AT, and daily ARH in Hubei province from December 1, 2019 to February 11, 2020.
Fig. 3
Fig. 3
Effect plots for the impact of (a) AT and (b) ARH on the daily counts of COVID-19.
Fig. 4
Fig. 4
The forest plot (a) and spatial distribution (b) of IRRs of AT with ARH fixed at its median in all the provinces in China.
Fig. 5
Fig. 5
The forest plot (a) and spatial distribution (b) of IRRs of ARH with AT fixed at its median in all provinces in China.
See this image and copyright information in PMC

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