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Discovering Correlations between the COVID-19 Epidemic Spread and Climate

Author

Listed:
  • Shaofu Lin

    (Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China
    Beijing Institute of Smart City, 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)

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.

Suggested Citation

  • Shaofu Lin & Yu Fu & Xiaofeng Jia & Shimin Ding & Yongxing Wu & Zhou Huang, 2020. "Discovering Correlations between the COVID-19 Epidemic Spread and Climate," IJERPH, MDPI, vol. 17(21), pages 1-14, October.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:21:p:7958-:d:437060
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    Citations

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    Cited by:

    1. David Meintrup & Martina Nowak-Machen & Stefan Borgmann, 2021. "Nine Months of COVID-19 Pandemic in Europe: A Comparative Time Series Analysis of Cases and Fatalities in 35 Countries," IJERPH, MDPI, vol. 18(12), pages 1-17, June.
    2. Yu Fu & Shaofu Lin & Zhenkai Xu, 2022. "Research on Quantitative Analysis of Multiple Factors Affecting COVID-19 Spread," IJERPH, MDPI, vol. 19(6), pages 1-13, March.
    3. Diego Galvan & Luciane Effting & Hágata Cremasco & Carlos Adam Conte-Junior, 2020. "Can Socioeconomic, Health, and Safety Data Explain the Spread of COVID-19 Outbreak on Brazilian Federative Units?," IJERPH, MDPI, vol. 17(23), pages 1-16, November.

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