DTU Management, Department of Technology, Management and Economics, Technical University of Denmark, Demark; European Centre for Environment and Human Health, University of Exeter, UK; Alan Turing Institute, London, UK.
European Centre for Environment and Human Health, University of Exeter, UK.
Soc Sci Med. 2021 Nov;289:114413. doi: 10.1016/j.socscimed.2021.114413. Epub 2021 Sep 23.
This paper aims to understand the relationship between area level deprivation and monthly COVID-19 cases in England in response to government policy throughout 2020. The response variable is monthly reported COVID-19 cases at the Middle Super Output Area (MSOA) level by Public Health England, with Index of Multiple Deprivation (IMD), ethnicity (percentage of the population across 5 ethnicity categories) and the percentage of the population older than 70 years old and time as predictors. A GEE population-averaged panel-data model was employed to model trends in monthly COVID-19 cases with the population of each MSOA included as the exposure variable. Area level deprivation is significantly associated with COVID-19 cases from March 2020; however, this relationship is reversed in December 2020. Follow up analysis found that this reversal was maintained when controlling for the novel COVID-19 variant outbreak in the South East of England. This analysis indicates that changes in the role of deprivation and monthly reported COVID-19 over time cases may be linked to two government policies: (1) the premature easing of national restrictions in July 2020 when cases were still high in the most deprived areas in England and (2) the introduction of a regional tiered system in October predominantly in the North of England. The analysis adds to the evidence showing that deprivation is a key driver of COVID-19 outcomes and highlights the unintended negative impact of government policy.
本文旨在了解英格兰地区贫困水平与 2020 年期间政府政策下每月 COVID-19 病例之间的关系。因变量是英格兰公共卫生部报告的每月中超级街区(MSOA)层面的 COVID-19 病例,自变量为综合贫困指数(IMD)、种族(5 个种族类别的人口百分比)、70 岁以上人口百分比和时间。采用广义估计方程(GEE)人群平均面板数据模型,以每个 MSOA 的人口作为暴露变量,对每月 COVID-19 病例的趋势进行建模。2020 年 3 月,地区贫困水平与 COVID-19 病例显著相关;但在 2020 年 12 月,这种关系发生了逆转。后续分析发现,当控制英格兰东南部新型 COVID-19 变异爆发时,这种逆转仍然存在。该分析表明,随着时间的推移,贫困程度和每月报告 COVID-19 病例之间作用的变化可能与两项政府政策有关:(1)2020 年 7 月,当英格兰最贫困地区的病例仍然居高不下时,过早放宽全国限制;(2)2020 年 10 月主要在英格兰北部推出的区域分层系统。该分析增加了贫困是 COVID-19 结果的关键驱动因素的证据,并强调了政府政策的意外负面影响。