Exploring the Factors Influencing the Spread of COVID-19 Within Residential Communities Using a Big Data Approach: A Case Study of Beijing

Exploring the Factors Influencing the Spread of COVID-19 Within Residential Communities Using a Big Data Approach: A Case Study of Beijing

The COVID-19 pandemic has profoundly influenced urban planning and disease management in residential areas. Focusing on Beijing as a case study (3898 communities), this research develops a big data analytics framework integrating anonymized mobile phone signals (China Mobile), location-based service...

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Bibliographic Details
Main Authors: Yang Li, Xiaoming Sun, Huiyan Chen, Hong Zhang, Yinong Li, Wenqi Lin, Linan Ding
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Buildings
Subjects:
big data
residential communities
transmission factors
risk prediction
planning and governance
Online Access:https://www.mdpi.com/2075-5309/15/13/2186
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Summary:The COVID-19 pandemic has profoundly influenced urban planning and disease management in residential areas. Focusing on Beijing as a case study (3898 communities), this research develops a big data analytics framework integrating anonymized mobile phone signals (China Mobile), location-based services (AMAP.com), and municipal health records to quantify COVID-19 transmission dynamics. Using logistic regression, we analyzed 15 indicators across four dimensions: mobility behavior, host demographics, spatial characteristics, and facility accessibility. Our analysis reveals three key determinants: (1) Population aged 65 and above (OR = 62.8, <i>p</i> < 0.001) and (2) housing density (OR = 9.96, <i>p</i> = 0.026) significantly increase transmission risk, while (3) population density exhibits a paradoxical negative effect (β = −3.98, <i>p</i> < 0.001) attributable to targeted interventions in high-density zones. We further construct a validated risk prediction model (AUC = 0.7; 95.97% accuracy) enabling high-resolution spatial targeting of non-pharmaceutical interventions (NPIs). The framework provides urban planners with actionable strategies—including senior activity scheduling and ventilation retrofits—while advancing scalable methodologies for infectious disease management in global urban contexts.
ISSN:2075-5309

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