Discovering Correlations between the COVID-19 Epidemic Spread and Climate

Shaofu Lin, Yu Fu, Xiaofeng Jia, Shimin Ding, Yongxing Wu and Zhou Huang
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Shaofu Lin: Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China
Yu Fu: Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China
Xiaofeng Jia: Beijing Big Data Center, Beijing 100142, China
Shimin Ding: Green Intelligence Environmental School, Yangtze Normal University, Chongqing 408107, China
Yongxing Wu: Institute of Remote Sensing and Geographical Information Systems, School of Earth and Space Sciences, Peking University, Beijing 100871, China
Zhou Huang: Institute of Remote Sensing and Geographical Information Systems, School of Earth and Space Sciences, Peking University, Beijing 100871, China

IJERPH, 2020, vol. 17, issue 21, 1-14

Abstract: The outbreak of Corona Virus Disease 2019 (COVID-19) has affected the lives of people all over the world. It is particularly urgent and important to analyze the epidemic spreading law and support the implementation of epidemic prevention measures. It is found that there is a moderate to high correlations between the number of newly diagnosed cases per day and temperature and relative humidity in countries with more than 10,000 confirmed cases worldwide. In this paper, the correlation between temperature/relative humidity and the number of newly diagnosed cases is obvious. Governments can adjust the epidemic prevention measures according to climate change, which will more effectively control the spread of COVID-19.

Keywords: multiple linear regression; COVID-19; climate correlation (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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