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衡量英国城镇中黑人、亚裔及其他族裔群体接触新冠病毒感染社区的情况。

Measuring the exposure of Black, Asian and other ethnic groups to COVID-infected neighbourhoods in English towns and cities.

作者信息

Harris Richard, Brunsdon Chris

机构信息

School of Geographical Sciences, University of Bristol, University Road, Bristol, BS8 1SS UK.

National Centre for Geocomputation, Maynooth University, Maynooth, Co. Kildare Ireland.

出版信息

Appl Spat Anal Policy. 2022;15(3):621-646. doi: 10.1007/s12061-021-09400-8. Epub 2021 Sep 3.

Abstract

Drawing on the work of The Doreen Lawrence Review-a report on the disproportionate impact of COVID-19 on Black, Asian and minority ethnic communities in the UK-this paper develops an index of exposure, measuring which ethnic groups have been most exposed to COVID-19 infected residential neighbourhoods during the first and second waves of the pandemic in England. The index is based on a Bayesian Poisson model with a random intercept in the linear predictor, allowing for extra-Poisson variation at neighbourhood and town/city scales. This permits within-city differences to be decoupled from broader regional trends in the disease. The research finds that members of ethnic minority groups can be living in areas with higher infection rates but also that the risk of exposure is distributed unevenly across these groups. Initially, in the first wave, the disease disproportionately affected Black residents but, as the pandemic has progressed, especially the Pakistani but also the Bangladeshi and Indian groups have had the highest exposure. This higher exposure of the Pakistani group is not straightforwardly a function of neighbourhood deprivation because it is present across a range of average house prices. We find evidence to support the view, expressed in The Doreen Lawrence Review, that it is linked to occupational and environmental exposure, particularly residential density but, having allowed for these factors, differences between the towns and cities remain.

摘要

借鉴《多琳·劳伦斯评论》的研究成果——一份关于新冠疫情对英国黑人、亚裔和少数族裔社区造成不成比例影响的报告——本文编制了一个暴露指数,用以衡量在英格兰疫情的第一波和第二波期间,哪些族裔群体接触新冠病毒感染居民区的情况最为严重。该指数基于一个贝叶斯泊松模型,线性预测器中有一个随机截距,考虑到了邻里和城镇/城市尺度上的超泊松变异。这使得城市内部的差异能够与该疾病更广泛的区域趋势脱钩。研究发现,少数族裔群体成员可能生活在感染率较高的地区,但接触风险在这些群体中的分布并不均匀。最初,在第一波疫情中,该疾病对黑人居民的影响尤为严重,但随着疫情的发展,尤其是巴基斯坦群体,还有孟加拉和印度群体,接触风险最高。巴基斯坦群体的这种较高接触风险并非直接取决于邻里贫困程度,因为在一系列平均房价水平的地区都存在这种情况。我们找到证据支持了《多琳·劳伦斯评论》中表达的观点,即这与职业和环境接触有关,尤其是居住密度,但在考虑了这些因素之后,城镇和城市之间的差异仍然存在。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b03c/8414459/8451737ce538/12061_2021_9400_Fig1_HTML.jpg

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