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纽约市社区中 COVID-19 病例阳性率的差异:社会经济因素和流动性。

Differential COVID-19 case positivity in New York City neighborhoods: Socioeconomic factors and mobility.

机构信息

Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA.

ICAP, Mailman School of Public Health, Columbia University, New York, NY, USA.

出版信息

Influenza Other Respir Viruses. 2021 Mar;15(2):209-217. doi: 10.1111/irv.12816. Epub 2020 Oct 14.

Abstract

BACKGROUND

New York City (NYC) has been one of the hotspots of the COVID-19 pandemic in the United States. By the end of April 2020, close to 165 000 cases and 13 000 deaths were reported in the city with considerable variability across the city's ZIP codes.

OBJECTIVES

In this study, we examine: (a) the extent to which the variability in ZIP code-level case positivity can be explained by aggregate markers of socioeconomic status (SES) and daily change in mobility; and (b) the extent to which daily change in mobility independently predicts case positivity.

METHODS

COVID-19 case positivity by ZIP code was modeled using multivariable linear regression with generalized estimating equations to account for within-ZIP clustering. Daily case positivity was obtained from NYC Department of Health and Mental Hygiene and measures of SES were based on data from the American Community Survey. Changes in human mobility were estimated using anonymized aggregated mobile phone location systems.

RESULTS

Our analysis indicates that the socioeconomic markers considered together explained 56% of the variability in case positivity through April 1 and their explanatory power decreased to 18% by April 30. Changes in mobility during this time period are not likely to be acting as a mediator of the relationship between ZIP-level SES and case positivity. During the middle of April, increases in mobility were independently associated with decreased case positivity.

CONCLUSIONS

Together, these findings present evidence that heterogeneity in COVID-19 case positivity during NYC's spring outbreak was largely driven by residents' SES.

摘要

背景

纽约市(NYC)是美国 COVID-19 大流行的热点地区之一。到 2020 年 4 月底,该市报告了近 16.5 万例病例和 1.3 万例死亡,全市邮政编码之间存在相当大的差异。

目的

在这项研究中,我们研究了:(a)邮政编码层面病例阳性率的差异在多大程度上可以用社会经济地位(SES)的综合指标和每日流动性变化来解释;(b)每日流动性变化在多大程度上独立预测病例阳性率。

方法

使用广义估计方程的多变量线性回归对邮政编码的 COVID-19 病例阳性率进行建模,以考虑邮政编码内的聚类。每日病例阳性率来自纽约市卫生和精神卫生部,SES 指标基于美国社区调查的数据。使用匿名聚合移动电话位置系统来估计人类流动性的变化。

结果

我们的分析表明,考虑到的社会经济指标共同解释了 4 月 1 日前病例阳性率的 56%,到 4 月 30 日其解释能力下降到 18%。在此期间,流动性的变化不太可能是邮政编码层面 SES 和病例阳性率之间关系的中介因素。在 4 月中旬,流动性的增加与病例阳性率的降低独立相关。

结论

这些发现共同表明,在纽约市春季疫情中,COVID-19 病例阳性率的异质性在很大程度上是由居民的 SES 驱动的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1c22/7902249/ea10329f70b9/IRV-15-209-g001.jpg

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