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路易斯安那州普查区社会脆弱性与 COVID-19 发病率之间的关系。

The Relationship Between Social Vulnerability and COVID-19 Incidence Among Louisiana Census Tracts.

机构信息

Epidemiology Program, Louisiana State University Health Sciences Center School of Public Health, New Orleans, LA, United States.

Division of Global HIV/TB, Centers for Disease Control and Prevention, Epidemiology and Surveillance Branch, Atlanta, GA, United States.

出版信息

Front Public Health. 2021 Jan 20;8:617976. doi: 10.3389/fpubh.2020.617976. eCollection 2020.

Abstract

To examine the association between the Centers for Disease Control and Prevention (CDC)'s Social Vulnerability Index (SVI) and COVID-19 incidence among Louisiana census tracts. An ecological study comparing the CDC SVI and census tract-level COVID-19 case counts was conducted. Choropleth maps were used to identify census tracts with high levels of both social vulnerability and COVID-19 incidence. Negative binomial regression with random intercepts was used to compare the relationship between overall CDC SVI percentile and its four sub-themes and COVID-19 incidence, adjusting for population density. In a crude stratified analysis, all four CDC SVI sub-themes were significantly associated with COVID-19 incidence. Census tracts with higher levels of social vulnerability were associated with higher COVID-19 incidence after adjusting for population density (adjusted RR: 1.52, 95% CI: 1.41-1.65). The results of this study indicate that increased social vulnerability is linked with COVID-19 incidence. Additional resources should be allocated to areas of increased social disadvantage to reduce the incidence of COVID-19 in vulnerable populations.

摘要

为了研究疾病控制与预防中心(CDC)的社会脆弱性指数(SVI)与路易斯安那州普查区 COVID-19 发病率之间的关系。 进行了一项比较 CDC SVI 和普查区 COVID-19 病例计数的生态学研究。 使用面域图来识别社会脆弱性和 COVID-19 发病率均较高的普查区。 采用具有随机截距的负二项式回归,比较总体 CDC SVI 百分位数及其四个子主题与 COVID-19 发病率之间的关系,并根据人口密度进行调整。 在未经调整的分层分析中,所有四个 CDC SVI 子主题均与 COVID-19 发病率显著相关。 调整人口密度后,社会脆弱性水平较高的普查区与 COVID-19 发病率较高相关(调整后的 RR:1.52,95%CI:1.41-1.65)。 这项研究的结果表明,社会脆弱性的增加与 COVID-19 的发病率有关。 应向社会劣势增加的地区分配更多资源,以减少弱势群体中 COVID-19 的发病率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7f0d/7856141/8151bb88cc25/fpubh-08-617976-g0001.jpg

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