ArticleSustainable cities and society2022
Spatial disparities of self-reported COVID-19 cases and influencing factors in Wuhan, China.
Article in Sustainable cities and society, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
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Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Effects of the built environment and human factors on the spread of COVID-19: A systematic literature review.The Science of the total environment · 2022Pooled it
- Features of the land use and COVID-19 cases and deaths in urban and land counties in Poland throughout the pandemic: a machine learning approach.BMC public health · 2026Article
- Potential physical distance in the open urban grey space of city counties in Poland and COVID-19 cases and deaths throughout the pandemic.Archives of public health = Archives belges de sante publique · 2025Article
- Temporal and Spatial Effects of Extreme Drought Events on Human Epidemics over Ancient China in 1784-1787 CE.Environmental health : a global access science source · 2025Article
- Long-term spatial-temporal evolution of hepatitis C burden in eastern China: a retrospective case analysis from Wuxi City.Frontiers in public health · 2025Article
- Big data-driven spatio-temporal heterogeneity analysis of Beijing's catering service industry during the COVID-19 pandemic.Scientific reports · 2024Article
- Tokyo's COVID-19: An urban perspective on factors influencing infection rates in a global city.Sustainable cities and society · 2023Article
- Pandemic vulnerability index of US cities: A hybrid knowledge-based and data-driven approach.Sustainable cities and society · 2023Article
- Dataset for developing optimal headway-based bus dispatching strategy during epidemic outbreaks.Data in brief · 2023Article
- Spatiotemporal Patterns of the Omicron Wave of COVID-19 in the United States.Tropical medicine and infectious disease · 2023Article
- Post COVID-19 pandemic recovery of intracity human mobility in Wuhan: Spatiotemporal characteristic and driving mechanism.Travel behaviour & society · 2023Article
- Integration of Moran's I, geographically weighted regression (GWR), and ordinary least square (OLS) models in spatiotemporal modeling of COVID-19 outbreak in Qom and Mazandaran Provinces, Iran.Modeling earth systems and environment · 2023Article
- Spatial co-location patterns between early COVID-19 risk and urban facilities: a case study of Wuhan, China.Frontiers in public health · 2023Article
- Are the epidemic prevention facilities effective? How cities should choose epidemic prevention facilities: Taking Wuhan as an example.Frontiers in public health · 2023Article
- Spatial impacts of the intercity flow of long stay international visitors based on mobile phone data in Yangtze River Delta, China.PloS one · 2023Article
- Effect of COVID-19 lockdowns on city-center and suburban housing markets: Evidence from Hangzhou, China.Journal of Asian economics · 2022Article
- Research Progress and Improvement Ideas of Anti-Epidemic Resilience in China's Urban Communities.International journal of environmental research and public health · 2022Review
- Spatio-Temporal Variation and Its Driving Forces of Soil Organic Carbon along an Urban-Rural Gradient: A Case Study of Beijing.International journal of environmental research and public health · 2022Article
- Impact of built environment on residential online car-hailing trips: Based on MGWR model.PloS one · 2022Article
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Authors and funding
7 authors.
Funding
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Abstract
The lack of detailed COVID-19 cases at a fine spatial resolution restricts the investigation of spatial disparities of its attack rate. Here, we collected nearly one thousand self-reported cases from a social media platform during the early stage of COVID-19 epidemic in Wuhan, China. We used kernel density estimation (KDE) to explore spatial disparities of epidemic intensity and adopted geographically weighted regression (GWR) model to quantify influences of population dynamics, transportation, and social interactions on COVID-19 epidemic. Results show that self-reported COVID-19 cases concentrated in commercial centers and populous residential areas. Blocks with higher population density, higher aging rate, more metro stations, more main roads, and more commercial point-of-interests (POIs) have a higher density of COVID-19 cases. These five explanatory variables explain 76% variance of self-reported cases using an OLS model. Commercial POIs have the strongest influence, which increase COVID-19 cases by 28% with one standard deviation increase. The GWR model performs better than OLS model with the adjusted
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