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美国新冠疫苗不平等问题的多维人口分析:一项系统综述

Multidimensional Demographic Analyses of COVID-19 Vaccine Inequality in the United States: A Systematic Review.

作者信息

Karimi Seyed M, Khan Sirajum Munira, Moghadami Mana, Parh Md Yasin Ali, Shakib Shaminul H, Zarei Hamid, Poursafargholi Sepideh, Little Bert B

机构信息

Department of Health Management and Systems Sciences, School of Public Health and Information Sciences, University of Louisville, Louisville, KY 40202, USA.

Department of Bioinformatics and Biostatistics, School of Public Health and Information Sciences, University of Louisville, Louisville, KY 40202, USA.

出版信息

Healthcare (Basel). 2025 Jan 13;13(2):139. doi: 10.3390/healthcare13020139.

Abstract

BACKGROUND

COVID-19 vaccination uptake is associated with demographic characteristics such as age, sex, and ethnicity-race in the United States (U.S.). Prior research predominantly analyzed COVID-19 vaccination uptake unidimensionally, limiting insights into multidimensional demographic inequalities. Multidimensional studies provide a closer insight into vaccination inequality and assist in designing more effective vaccination strategies.

OBJECTIVES

Review descriptive studies of the COVID-19 vaccination uptake across combinations of at least two of the three key demographic characteristics: age, sex, and ethnicity-race in the U.S.

METHODS

A systematic review was performed using the Joanna Briggs Institute methodology and adhering to the PRISMA-ScR principles for reporting. Six impartial reviewers examined all of the papers. The data were obtained using a tailored data extraction template.

RESULTS

A total of 2793 records were initially downloaded, 461 of them were dropped for duplication, and 2332 were reviewed. Based on the title and abstract reviews, 2115 records were excluded. After reviewing the full text of the remaining records, 212 more records were excluded. The remaining six records were reviewed to identify and compare their population, study period, data, the studied dose number, methodology, and results.

CONCLUSIONS

Multidimensional COVID-19 vaccine uptake analyses are rare and mostly focused on the dose-one vaccination. Improving researchers' access to immunization registry data while preserving data security is a prerequisite for such analyses.

摘要

背景

在美国,新冠病毒病(COVID-19)疫苗接种情况与年龄、性别和种族等人口统计学特征相关。先前的研究主要对COVID-19疫苗接种情况进行单维度分析,限制了对多维人口统计学不平等现象的深入了解。多维研究能更深入地洞察疫苗接种不平等问题,并有助于设计更有效的疫苗接种策略。

目的

综述关于美国年龄、性别和种族这三个关键人口统计学特征中至少两个特征组合下COVID-19疫苗接种情况的描述性研究。

方法

采用乔安娜·布里格斯研究所的方法进行系统综述,并遵循PRISMA-ScR报告原则。六名公正的评审员审查了所有论文。数据通过定制的数据提取模板获取。

结果

最初共下载了2793条记录,其中461条因重复而被剔除,2332条进行了审查。基于标题和摘要审查,排除了2115条记录。在审查其余记录的全文后,又排除了212条记录。对其余六条记录进行审查,以识别和比较其研究人群、研究时期、数据、研究的剂量数、方法和结果。

结论

多维COVID-19疫苗接种情况分析很少见,且大多集中在第一剂疫苗接种上。在保护数据安全的同时,改善研究人员获取免疫登记数据的机会是进行此类分析的前提条件。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/14e2/11765134/d7aa703638c7/healthcare-13-00139-g001.jpg

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