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Exploring the Relationship among Human Activities, COVID-19 Morbidity, and At-Risk Areas Using Location-Based Social Media Data: Knowledge about the Early Pandemic Stage in Wuhan

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  • Mengyue Yuan

    (School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430072, China
    National Engineering Research Center for Geographic Information System, China University of Geosciences (Wuhan), Wuhan 430079, China)

  • Tong Liu

    (School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430072, China
    National Engineering Research Center for Geographic Information System, China University of Geosciences (Wuhan), Wuhan 430079, China)

  • Chao Yang

    (National Engineering Research Center for Geographic Information System, China University of Geosciences (Wuhan), Wuhan 430079, China)

Abstract

It is significant to explore the morbidity patterns and at-risk areas of the COVID-19 outbreak in megacities. In this paper, we studied the relationship among human activities, morbidity patterns, and at-risk areas in Wuhan City. First, we excavated the activity patterns from Sina Weibo check-in data during the early COVID-19 pandemic stage (December 2019~January 2020) in Wuhan. We considered human-activity patterns and related demographic information as the COVID-19 influencing determinants, and we used spatial regression models to evaluate the relationships between COVID-19 morbidity and the related factors. Furthermore, we traced Weibo users’ check-in trajectories to characterize the spatial interaction between high-morbidity residential areas and activity venues with POI (point of interest) sites, and we located a series of potential at-risk places in Wuhan. The results provide statistical evidence regarding the utility of human activity and demographic factors for the determination of COVID-19 morbidity patterns in the early pandemic stage in Wuhan. The spatial interaction revealed a general transmission pattern in Wuhan and determined the high-risk areas of COVID-19 transmission. This article explores the human-activity characteristics from social media check-in data and studies how human activities played a role in COVID-19 transmission in Wuhan. From that, we provide new insights for scientific prevention and control of COVID-19.

Suggested Citation

  • Mengyue Yuan & Tong Liu & Chao Yang, 2022. "Exploring the Relationship among Human Activities, COVID-19 Morbidity, and At-Risk Areas Using Location-Based Social Media Data: Knowledge about the Early Pandemic Stage in Wuhan," IJERPH, MDPI, vol. 19(11), pages 1-22, May.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:11:p:6523-:d:825470
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    1. Wei Lu & Yuechen Li & Rongkun Zhao & Bo He & Zihua Qian, 2022. "Spatial Pattern and Fairness Measurement of Educational Resources in Primary and Middle Schools: A Case Study of Chengdu–Chongqing Economic Circle," IJERPH, MDPI, vol. 19(17), pages 1-23, August.

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