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剖析差异:路易斯安那州不同时期、地域、社会脆弱性及政治倾向下新冠疫情异质差异的案例研究

Disaggregating disparities: A case study of heterogenous COVID-19 disparities across waves, geographies, social vulnerability, and political lean in Louisiana.

作者信息

Schnake-Mahl Alina, Bilal Usama

机构信息

Urban Health Collaborative, Drexel Dornsife School of Public Health, Philadelphia, PA, USA.

Department of Health Management and Policy, Drexel Dornsife School of Public Health, Philadelphia, PA, USA.

出版信息

Prev Med Rep. 2022 Aug;28:101833. doi: 10.1016/j.pmedr.2022.101833. Epub 2022 May 26.

Abstract

While the first wave of COVID-19 primarily impacted urban areas, subsequent waves were more widespread. Most analysis of Covid-19 rates examine state or metropolitan areas, ignoring potential heterogeneity within states and metro areas, over time, and between populations with differing contextual and compositional features. In this study, we compare spatial and temporal trends in Covid-19 cases and deaths in Louisiana, USA, over time and across populations and geographies (New Orleans, other urban areas, suburban, rural) and parish-level political lean. We employ publicly available longitudinal census tract and parish-level Covid-19 data reported from February 27th, 2020 to October 27th, 2021. We find that incidence and mortality rates were initially highest in New Orleans and Democratic areas and higher in other geographies and more conservative areas during subsequent waves. We also find wide relative disparities during the first wave, where increased social vulnerability was associated with increased positivity and incidence across geographies and political contexts. However, relative disparities diverged by geography and political lean and outcome across the remaining waves. This work draws attention to the differential rates of Covid-19 cases and deaths by geography, time, and population throughout the pandemic, and importance of political and geographic boundaries for rates of Covid-19.

摘要

虽然新冠疫情的第一波主要影响了城市地区,但后续几波的影响范围更广。大多数对新冠疫情感染率的分析考察的是州或大都市区,忽略了州和大都市区内部、不同时间以及具有不同背景和构成特征的人群之间可能存在的异质性。在本研究中,我们比较了美国路易斯安那州新冠病例和死亡的空间和时间趋势,涉及不同时间、不同人群和地理区域(新奥尔良、其他城市地区、郊区、农村)以及教区层面的政治倾向。我们使用了从2020年2月27日至2021年10月27日报告的公开可用的纵向普查区和教区层面的新冠疫情数据。我们发现,发病率和死亡率最初在新奥尔良和民主党地区最高,在后续几波中,其他地理区域和更保守的地区则更高。我们还发现在第一波疫情期间存在很大的相对差异,即社会脆弱性增加与不同地理区域和政治背景下的阳性率和发病率上升相关。然而,在后续几波疫情中,相对差异因地理区域、政治倾向和结果而有所不同。这项工作提请人们关注整个疫情期间新冠病例和死亡按地理区域、时间和人群划分的不同比率,以及政治和地理边界对新冠疫情感染率的重要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eaa8/9151737/3dd8fcbc1938/gr1.jpg

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