ArticleComputational urban science2021
Exploring temporal varying demographic and economic disparities in COVID-19 infections in four U.S. areas: based on OLS, GWR, and random forest models.
Article in Computational urban science, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Study on the spatial-temporal evolution and influencing factors of AIDS incidence in China from 2006 to 2022.BMC infectious diseases · 2025Article
- 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
- Development of a composite regional vulnerability index and its relationship with the impacts of the COVID-19 pandemic.Computational urban science · 2023Article
- Tempo-Spatial Modelling of the Spread of COVID-19 in Urban Spaces.International journal of environmental research and public health · 2022Article
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Authors and funding
3 authors.
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Abstract
Although studies have previously investigated the spatial factors of COVID-19, most of them were conducted at a low resolution and chose to limit their study areas to high-density urbanized regions. Hence, this study aims to investigate the economic-demographic disparities in COVID-19 infections and their spatial-temporal patterns in areas with different population densities in the United States. In particular, we examined the relationships between demographic and economic factors and COVID-19 density using ordinary least squares, geographically weighted regression analyses, and random forest based on zip code-level data of four regions in the United States. Our results indicated that the demographic and economic disparities are significant. Moreover, several areas with disadvantaged groups were found to be at high risk of COVID19 infection, and their infection risk changed at different pandemic periods. The findings of this study can contribute to the planning of public health services, such as the adoption of smarter and comprehensive policies for allocating economic recovery resources and vaccines during a public health crisis.
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