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英格兰 COVID-19 死亡率与社会经济和环境因素的空间不平等关系。

Spatial inequalities of COVID-19 mortality rate in relation to socioeconomic and environmental factors across England.

机构信息

Department of Geography, College of Science, Swansea University, Swansea SA28PP, United Kingdom; School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China.

Institute of Data Science, German Aerospace Center (DLR), Jena 07745, Germany.

出版信息

Sci Total Environ. 2021 Mar 1;758:143595. doi: 10.1016/j.scitotenv.2020.143595. Epub 2020 Nov 13.

DOI:10.1016/j.scitotenv.2020.143595
PMID:33218796
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7664354/
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 (R = 0.49 and R = 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'.

摘要

在这项研究中,我们旨在研究与英格兰社会经济和环境因素空间不平等相关的 COVID-19 死亡率的空间不平等。具体来说,我们首先探索了 COVID-19 死亡率与非 COVID-19 死亡率的空间模式。随后,我们建立了模型来研究社会经济和环境因素对英格兰 COVID-19 死亡率空间变化的贡献(N=317)。成功建立了两种新的空间回归模型规范来估计 COVID-19 死亡率(R=0.49 和 R=0.793)。英格兰 COVID-19 死亡率的空间不平等程度高于非 COVID-19 死亡率。尽管 COVID-19 死亡率和非 COVID-19 死亡率的全球空间关联为正,但在某些地区,COVID-19 死亡率和非 COVID-19 死亡率的局部空间关联为负。预计,医院可达性与 COVID-19 死亡率呈负相关。亚洲人比例、黑人比例和失业率与 COVID-19 死亡率呈正相关。更重要的是,相对湿度与 COVID-19 死亡率呈负相关。此外,在所估计的空间模型中,“特征向量空间滤波模型的随机效应规范”优于“空间自回归模型的矩阵指数空间规范”。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5341/7664354/9210a42599fc/gr4_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5341/7664354/892713696014/ga1_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5341/7664354/fae902a6e439/gr1_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5341/7664354/3c82a08538da/gr2_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5341/7664354/8a062a150f66/gr3_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5341/7664354/9210a42599fc/gr4_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5341/7664354/892713696014/ga1_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5341/7664354/fae902a6e439/gr1_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5341/7664354/3c82a08538da/gr2_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5341/7664354/8a062a150f66/gr3_lrg.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5341/7664354/9210a42599fc/gr4_lrg.jpg

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