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Correlation Analysis between Urban Elements and COVID-19 Transmission Using Social Media Data

Author

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  • Ru Wang

    (Department of Urban Planning, School of Urban Design, Wuhan University, Wuhan 430072, China)

  • Lingbo Liu

    (Department of Urban Planning, School of Urban Design, Wuhan University, Wuhan 430072, China
    Center for Geographic Analysis, Harvard University, Cambridge, MA 02138, USA)

  • Hao Wu

    (Department of Graphics and Digital Technology, School of Urban Design, Wuhan University, Wuhan 430072, China)

  • Zhenghong Peng

    (Department of Graphics and Digital Technology, School of Urban Design, Wuhan University, Wuhan 430072, China)

Abstract

The outbreak of the COVID-19 has become a worldwide public health challenge for contemporary cities during the background of globalization and planetary urbanization. However, spatial factors affecting the transmission of the disease in urban spaces remain unclear. Based on geotagged COVID-19 cases from social media data in the early stage of the pandemic, this study explored the correlation between different infectious outcomes of COVID-19 transmission and various factors of the urban environment in the main urban area of Wuhan, utilizing the multiple regression model. The result shows that most spatial factors were strongly correlated to case aggregation areas of COVID-19 in terms of population density, human mobility and environmental quality, which provides urban planners and administrators valuable insights for building healthy and safe cities in an uncertain future.

Suggested Citation

  • Ru Wang & Lingbo Liu & Hao Wu & Zhenghong Peng, 2022. "Correlation Analysis between Urban Elements and COVID-19 Transmission Using Social Media Data," IJERPH, MDPI, vol. 19(9), pages 1-17, April.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:9:p:5208-:d:801789
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    References listed on IDEAS

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    1. Sijia Li & Yilin Wang & Jia Xue & Nan Zhao & Tingshao Zhu, 2020. "The Impact of COVID-19 Epidemic Declaration on Psychological Consequences: A Study on Active Weibo Users," IJERPH, MDPI, vol. 17(6), pages 1-9, March.
    2. Heyuan You & Xin Wu & Xuxu Guo, 2020. "Distribution of COVID-19 Morbidity Rate in Association with Social and Economic Factors in Wuhan, China: Implications for Urban Development," IJERPH, MDPI, vol. 17(10), pages 1-14, May.
    3. Michelle C. Kondo & Jaime M. Fluehr & Thomas McKeon & Charles C. Branas, 2018. "Urban Green Space and Its Impact on Human Health," IJERPH, MDPI, vol. 15(3), pages 1-28, March.
    4. Shima Hamidi & Sadegh Sabouri & Reid Ewing, 2020. "Does Density Aggravate the COVID-19 Pandemic?," Journal of the American Planning Association, Taylor & Francis Journals, vol. 86(4), pages 495-509, October.
    5. Tisdell, Clement A., 2020. "Economic, social and political issues raised by the COVID-19 pandemic," Economic Analysis and Policy, Elsevier, vol. 68(C), pages 17-28.
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    Cited by:

    1. Maryam Sabir & Yazan Al-Tarshan & Cameron Snapp & Martin Brown & Roland Walker & Amy Han & Tatiana Kostrominova, 2023. "Analysis of COVID-19 Case Demographics and Disease Outcomes in Gary, Indiana," IJERPH, MDPI, vol. 20(18), pages 1-12, September.
    2. Yonggeng Xiong & Min Xu & Yan Zhao, 2024. "Resident Preferences for Urban Green Spaces in Response to Pandemic Public Health Emergency: A Case Study of Shanghai," Sustainability, MDPI, vol. 16(9), pages 1-25, April.

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