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Examining the Human Activity-Intensity Change at Different Stages of the COVID-19 Pandemic across Chinese Working, Residential and Entertainment Areas

Author

Listed:
  • Shuang Ma

    (College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China
    These authors contributed equally to this work.)

  • Kang Cao

    (College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China
    These authors contributed equally to this work.)

  • Shuangjin Li

    (Graduate School of Advanced Science and Engineering, Hiroshima University, Higashihiroshima 739-8529, Japan)

  • Yaozhi Luo

    (College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China)

  • Ke Wang

    (College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China)

  • Wei Liu

    (Institute for Health and Environment, Chongqing University of Science and Technology, Chongqing 401331, China)

  • Guohui Sun

    (Beijing Key Laboratory of Environment and Viral Oncology, Faculty of Environment and Life, Beijing University of Technology, Beijing 100124, China)

Abstract

The COVID-19 pandemic has already resulted in more than 6 million deaths worldwide as of December 2022. The COVID-19 has also been greatly affecting the activity of the human population in China and the world. It remains unclear how the human activity-intensity changes have been affected by the COVID-19 spread in China at its different stages along with the lockdown and relaxation policies. We used four days of Location-based services data from Tencent across China to capture the real-time changes in human activity intensity in three stages of COVID-19—namely, during the lockdown, at the first stage of work resuming and at the stage of total work resuming—and observed the changes in different land use categories. We applied the mean decrease Gini (MDG) approach in random forest to examine how these changes are influenced by land attributes, relying on the CART algorithm in Python. This approach was also compared with Geographically Weighted Regression (GWR). Our analysis revealed that the human activity intensity decreased by 22–35%, 9–16% and 6–15%, respectively, in relation to the normal conditions before the spread of COVID-19 during the three periods. The human activity intensity associated with commercial sites, sports facilities/gyms and tourism experienced the relatively largest contraction during the lockdown. During the relaxations of restrictions, government institutions showed a 13.89% rise in intensity at the first stage of work resuming, which was the highest rate among all the working sectors. Furthermore, the GDP and road junction density were more influenced by the change in human activity intensity for all land use categories. The bus stop density was importantly associated with mixed-use land recovery during the relaxing stages, while the coefficient of density of population in entertainment land were relatively higher at these two stages. This study aims to provide additional support to investigate the human activity changes due to the spread of COVID-19 at different stages across different sectors.

Suggested Citation

  • Shuang Ma & Kang Cao & Shuangjin Li & Yaozhi Luo & Ke Wang & Wei Liu & Guohui Sun, 2022. "Examining the Human Activity-Intensity Change at Different Stages of the COVID-19 Pandemic across Chinese Working, Residential and Entertainment Areas," IJERPH, MDPI, vol. 20(1), pages 1-17, December.
    • Handle: RePEc:gam:jijerp:v:20:y:2022:i:1:p:390-:d:1015854
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