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住房条件不达标的情况与新型冠状病毒肺炎感染风险及疾病严重程度:一项回顾性队列研究

Substandard housing and the risk of COVID-19 infection and disease severity: A retrospective cohort study.

作者信息

Robb Katharine, Ahmed Rowana, Wong John, Ladd Elissa, de Jong Jorrit

机构信息

Bloomberg Center for Cities, Harvard Kennedy School, Cambridge, MA, USA.

School of Nursing, MGH Institute of Health Professions, Boston, MA, USA.

出版信息

SSM Popul Health. 2024 Feb 13;25:101629. doi: 10.1016/j.ssmph.2024.101629. eCollection 2024 Mar.

Abstract

In this study we examine associations between substandard housing and the risk of COVID-19 infection and severity during the first year of the pandemic by linking individual-level housing and clinical datasets. Residents of Chelsea, Massachusetts who were tested for COVID-19 at any Mass General Brigham testing site and who lived at a property that had received a city housing inspection were included (N = 2873). Chelsea is a densely populated city with a high prevalence of substandard housing. Inspected properties with housing code violations were considered substandard; inspected properties without violations were considered adequate. COVID-19 infection was defined as any positive PCR test, and severe disease defined as hospitalization with COVID-19. We used a propensity score design to match individuals on variables including age, race, sex, and income. In the severity model, we also matched on ten comorbidities. We estimated the risk of COVID-19 infection and severity associated with substandard housing using Cox Proportional Hazards models for lockdown, the first phase of reopening, and the full study period. In our sample, 32% (919/2873) of individuals tested positive for COVID-19 and 5.9% (135/2297) had severe disease. During lockdown, substandard housing was associated with a 48% increased risk of COVID-19 infection (95%CI 1.1-2.0, p = 0.006). Through Phase 1 reopening, substandard housing was associated with a 39% increased infection risk (95%CI 1.1-1.8, p = 0.020). The difference in risk attenuated over the full study period. There was no difference in severe disease risk between the two groups. The increased risk, observed only during lockdown and early reopening - when residents were most exposed to their housing - strengthens claims that substandard housing conveys higher infection risk. The results demonstrate the value of combining cross-sector datasets. Existing city housing data can be leveraged 1) to identify and prioritize high-risk areas for future pandemic response, and 2) for longer-term housing solutions.

摘要

在本研究中,我们通过将个人层面的住房和临床数据集相链接,考察了在疫情第一年中,不合标准住房与感染新冠病毒以及病情严重程度之间的关联。研究纳入了在马萨诸塞州布莱根妇女医院的任何检测点接受过新冠病毒检测、且居住在接受过城市住房检查的房产中的马萨诸塞州切尔西居民(N = 2873)。切尔西是一个人口密集的城市,不合标准住房的比例很高。被检查出存在住房法规违规的房产被视为不合标准;未被查出违规的房产被视为符合要求。新冠病毒感染定义为任何PCR检测呈阳性,重症疾病定义为因新冠病毒住院。我们采用倾向得分设计,在年龄、种族、性别和收入等变量上对个体进行匹配。在重症模型中,我们还在十种合并症上进行了匹配。我们使用Cox比例风险模型,针对封锁期、重新开放的第一阶段以及整个研究期,估计了与不合标准住房相关的新冠病毒感染风险和重症风险。在我们的样本中,32%(919/2873)的个体新冠病毒检测呈阳性,5.9%(135/2297)患有重症疾病。在封锁期间,不合标准住房与新冠病毒感染风险增加48%相关(95%CI 1.1 - 2.0,p = 0.006)。在重新开放的第一阶段,不合标准住房与感染风险增加39%相关(95%CI 1.1 - 1.8,p = 0.020)。在整个研究期内,风险差异有所减弱。两组之间的重症疾病风险没有差异。仅在封锁期和重新开放初期观察到的风险增加——此时居民与住房的接触最为频繁——强化了这样的观点,即不合标准住房带来更高的感染风险。研究结果证明了整合跨部门数据集的价值。现有的城市住房数据可用于:1)识别未来疫情应对的高风险区域并确定其优先级,以及2)制定长期住房解决方案。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a199/10879830/00cc9d838777/gr1.jpg

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