Sun, Yeran and Hu, Xuke and Xie, Jing (2020) Spatial inequalities of COVID-19 mortality rate in relation to socioeconomic and environmental factors across England. Science of the Total Environment, p. 143595. Elsevier. doi: 10.1016/j.scitotenv.2020.143595. ISSN 0048-9697.
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Abstract
In this study, we aimed to examine spatial inequalities of COVID-19 mortality rate in relation to spatial inequalities of socioeconomic and environmental factors across England. Specifically, we first explored spatial patterns of COVID-19 mortality rate in comparison to non-COVID-19 mortality rate. Subsequently, we established models to investigate contributions of socioeconomic and environmental factors to spatial variations of COVID-19 mortality rate across England (N = 317). Two newly developed specifications of spatial regression models were established successfully to estimate COVID-19 mortality rate (R2 = 0.49 and R2 = 0.793). The level of spatial inequalities of COVID-19 mortality is higher than that of non-COVID-19 mortality in England. Although global spatial association of COVID-19 mortality and non-COVID-19 mortality is positive, local spatial association of COVID-19 mortality and non-COVID-19 mortality is negative in some areas. Expectedly, hospital accessibility is negatively related to COVID-19 mortality rate. Percent of Asians, percent of Blacks, and unemployment rate are positively related to COVID-19 mortality rate. More importantly, relative humidity is negatively related to COVID-19 mortality rate. Moreover, among the spatial models estimated, the ‘random effects specification of eigenvector spatial filtering model’ outperforms the ‘matrix exponential spatial specification of spatial autoregressive model’.
Item URL in elib: | https://elib.dlr.de/140287/ | ||||||||||||||||
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Document Type: | Article | ||||||||||||||||
Title: | Spatial inequalities of COVID-19 mortality rate in relation to socioeconomic and environmental factors across England | ||||||||||||||||
Authors: |
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Date: | 2020 | ||||||||||||||||
Journal or Publication Title: | Science of the Total Environment | ||||||||||||||||
Refereed publication: | Yes | ||||||||||||||||
Open Access: | Yes | ||||||||||||||||
Gold Open Access: | No | ||||||||||||||||
In SCOPUS: | Yes | ||||||||||||||||
In ISI Web of Science: | Yes | ||||||||||||||||
DOI: | 10.1016/j.scitotenv.2020.143595 | ||||||||||||||||
Page Range: | p. 143595 | ||||||||||||||||
Publisher: | Elsevier | ||||||||||||||||
ISSN: | 0048-9697 | ||||||||||||||||
Status: | Published | ||||||||||||||||
Keywords: | COVID-19 mortality, Spatial disparities, Matrix exponential spatial specification model, Eigenvector spatial filtering model, Socioeconomic disadvantage | ||||||||||||||||
HGF - Research field: | Aeronautics, Space and Transport | ||||||||||||||||
HGF - Program: | Space | ||||||||||||||||
HGF - Program Themes: | Earth Observation | ||||||||||||||||
DLR - Research area: | Raumfahrt | ||||||||||||||||
DLR - Program: | R EO - Earth Observation | ||||||||||||||||
DLR - Research theme (Project): | R - Geoscientific remote sensing and GIS methods | ||||||||||||||||
Location: | Jena | ||||||||||||||||
Institutes and Institutions: | Institute of Data Science Institute of Data Science > Citizen Science | ||||||||||||||||
Deposited By: | Hu, Xuke | ||||||||||||||||
Deposited On: | 14 Jan 2021 13:16 | ||||||||||||||||
Last Modified: | 14 Jan 2021 13:16 |
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