Original Articles
28 April 2025
Vol. 20 No. 1 (2025)
Risk discrepancies in COVID-19-related community environments based on spatiotemporal monitoring
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All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
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The geo-inequality of COVID-19 risk has attracted a great deal of research attention. In this study, the spatial correlation between community environment and the incidence of COVID-19 cases in 30 Chinese cities is discussed. The spread of the disease is analyzed based on timing and spatial monitoring at the km2-grid level, with the use of publicly available data relating to housing prices, Gross Deomestic Product (GDP), medical facilities, consumer sites, public green spaces, and industrial sites. The results indicate substantial geographical variations in the distribution of COVID-19 communities in all 30 cities. Significant global bivariate spatial dependence was observed between the disease and housing prices (Moran’s I =0.099, p<0.01, z=488.6), medical facilities (Moran’s I = 0.349, p<0.01, z=1675.0), consumer sites (Moran’s I =0.369, p<0.01, z=1843.4), green space (Moran’s I =0.205, p<0.01, z=1037.8), and industrial sites (Moran’s I =0.234, p<0.01, z=1178.6). The risk of COVID-19 under the influence of GDP is further examined for cities with per capita GDPs from high to low ranging from 1.69 to 4.62 (1.69~3.74~4.62, 95% CI). These findings provide greater detail on the interplay between the infectious disease and community environments.
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How to Cite
Risk discrepancies in COVID-19-related community environments based on spatiotemporal monitoring. (2025). Geospatial Health, 20(1). https://doi.org/10.4081/gh.2025.1286
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