Roles of meteorological conditions in COVID-19 transmission on a worldwide scale

Biqing Chen; Hao Liang; Xiaomin Yuan; Yingying Hu; Miao Xu; Yating Zhao; Binfen Zhang; Fang Tian; Xuejun Zhu

(which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.03.16.20037168 doi: medRxiv preprint meteorological variables, i.e., air temperature, relative humidity, wind speed, and visibility, were collected as well as the confirmed case counts for each day between January 20 and March 11 for 430 cities and districts all over China. Those cities with over 50 confirmed cases monthly were taken as a discovery dataset to exclude the confounding effect due to purely imported cases. Four time points delay of the weather conditions from the day of epidemic situation evaluation were considered and compared to find the most possible time delay that best reveals the relationship between weather and COVID-19 outbreak. A multivariate polynomial regression model with factors of wind speed, relative humidity, and average air temperature was established, and then validated in 21 cities/ provinces in Italy, 21 cities/ provinces in Japan, and 51 other countries around the world. Finally, we use this model, in combination with weather forecast, to predict the probable outbreak in several high-latitude big cities around the world.