ArticleThe Science of the total environment2021
Spatial distribution characteristics of the COVID-19 pandemic in Beijing and its relationship with environmental factors.
Article in The Science of the total environment, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers, 2 of them syntheses that pooled it.
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Who cites it
47 citing papers in PubMed, 2 syntheses or guidelines pooled it, 102 citations in OpenAlex.
- 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
- Methods Used in the Spatial and Spatiotemporal Analysis of COVID-19 Epidemiology: A Systematic Review.International journal of environmental research and public health · 2022Pooled it
- Spatial heterogeneity of the association between fine particulate matter and lung cancer incidence in Hebei Province.Frontiers in oncology · 2026Article
- Harnessing Socio-Spatial Dynamics for Pandemic Resilience: Evidence from Kozhikode, India.One health (Amsterdam, Netherlands) · 2025Article
- Bayesian spatio-temporal analysis of the COVID-19 pandemic in Catalonia.Scientific reports · 2024Article
- Article
- Transmission chains of the first local outbreak cause by Delta VariantB.1.617.2 COVID-19 in Guangzhou, Southern China.BMC infectious diseases · 2024Article
- Visible minority status and occupation were associated with increased COVID-19 infection in Greater Vancouver British Columbia between June and November 2020: an ecological study.Frontiers in public health · 2024Article
- Article
- Structural Inequality and COVID-19 Mortality in Chicago: An Ecological Analysis.Journal of racial and ethnic health disparities · 2023Article
- Exploring the spatial pattern of community urban green spaces and COVID-19 risk in Wuhan based on a random forest model.Heliyon · 2023Article
- Neighborhood Governance and Happiness during the COVID-19 Pandemic: An Empirical Analysis of Wuhan's Lockdown.Behavioral sciences (Basel, Switzerland) · 2023Article
- Spatiotemporal pattern of COVID-19 mortality and its relationship with socioeconomic and environmental factors in England.Spatial and spatio-temporal epidemiology · 2023Article
- The impact of urban spatial environment on COVID-19: a case study in Beijing.Frontiers in public health · 2023Article
- Has the COVID-19 pandemic converged across countries?Empirical economics · 2023Article
- Population flow based spatial-temporal eigenvector filtering modeling for exploring effects of health risk factors on COVID-19.Sustainable cities and society · 2022Article
- Spatiotemporal clusters and the socioeconomic determinants of COVID-19 in Toronto neighbourhoods, Canada.Spatial and spatio-temporal epidemiology · 2022Article
- Investigating Linkages Between Spatiotemporal Patterns of the COVID-19 Delta Variant and Public Health Interventions in Southeast Asia: Prospective Space-Time Scan Statistical Analysis Method.JMIR public health and surveillance · 2022Article
- Very high-resolution remote sensing-based mapping of urban residential districts to help combat COVID-19.Cities (London, England) · 2022Article
- Geographically weighted regression model for physical, social, and economic factors affecting the COVID-19 pandemic spreading.Environmental science and pollution research international · 2022Article
Corrections and comments
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Authors and funding
8 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Investigating the spatial distribution characteristics of the coronavirus disease 2019 (COVID-19) and exploring the influence of environmental factors that drive it is the basis for formulating rational and efficient prevention and control countermeasures. Therefore, this study aims to analyze the spatial distribution characteristics of COVID-19 pandemic in Beijing and its relationship with the environmental factors. Based on the incidences of new local COVID-19 cases in Beijing from June 11 to July 5, the spatial clustering characteristics of the COVID-19 pandemic in Beijing was investigated using spatial autocorrelation analysis. The relation between COVID-19 cases and environmental factors was assessed using the Spearman correlation analysis. Finally, geographically weighted regression (GWR) was applied to explore the influence of environmental factors on the spatial distribution of COVID-19 cases. The results showed that the development of COVID-19 pandemic in Beijing from June 11 to July 5 could be divided into two stages. The first stage was the outward expansion from June 11 to June 21, and the second stage (from June 22 to July 5) was the growth of the transmission in areas with existing previous cases. In addition, there was a ring of low value clusters around the Xinfadi market. This area was the key area for prevention and control. Population density and distance to Xinfadi market were the most critical factors that explained the pandemic development. The findings of this study can provide useful information for the global fighting against COVID-19.
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