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危机中的治理:新冠疫情期间全球卫生治理的混合方法分析

Governance in Crisis: A Mixed-Methods Analysis of Global Health Governance During COVID-19.

作者信息

Abdel-Motaal Kadria Ali, Chun Sungsoo

机构信息

Institute of Global Health and Human Ecology, American University, New Cairo 11835, Egypt.

出版信息

Int J Environ Res Public Health. 2025 Aug 20;22(8):1305. doi: 10.3390/ijerph22081305.

DOI:10.3390/ijerph22081305
PMID:40869890
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12386743/
Abstract

BACKGROUND

The COVID-19 pandemic exposed major structural deficiencies in global health governance, including stark inequities in vaccine access, intervention timing, and mortality outcomes. While economic resources played a role, the influence of governance performance remains insufficiently examined. This study addresses a significant gap by integrating governance metrics with pandemic response data to assess how governance quality, independent of income level, affected national outcomes. Although the Oxford COVID-19 Government Response Tracker (OxCGRT) dataset has been widely used to document policy responses, this study offers a novel contribution by linking these policy interventions with governance performance and evaluating their joint effect on health outcomes and vaccine equity.

METHODS

This mixed-methods study combines quantitative analysis of global datasets with a qualitative literature review. Quantitative data were mainly obtained from the Oxford COVID-19 Government Response Tracker (OxCGRT), the World Bank's Worldwide Governance Indicators (WGIs), and World Bank/WHO databases. A governance performance index was constructed using two WGI components: Government Effectiveness and Regulatory Quality. Countries were grouped into high, medium, or low governance categories. Statistical tests included ANOVA, Kaplan Meier survival analysis, and multivariable OLS regression. The qualitative component reviewed 45 academic and institutional sources on governance performance during COVID-19.

RESULTS

Countries with high governance performance had earlier public health interventions, lower mortality, and broader vaccine coverage, independent of income level. Kaplan Meier analysis revealed faster school closures in these countries ( < 0.01). Multivariable regression showed governance remained a significant predictor after adjusting for income and health spending. Qualitative findings highlighted recurring weaknesses in legal enforceability, intergovernmental coordination, and global financing mechanisms.

CONCLUSIONS

Governance performance had a decisive impact on pandemic outcomes. The COVID-19 crisis revealed the need for robust governance systems capable of responding to complex emergencies that extend beyond the health sector into institutional, economic, and social spheres.

摘要

背景

新冠疫情暴露了全球卫生治理中的重大结构性缺陷,包括疫苗获取、干预时机和死亡率结果方面的严重不平等。虽然经济资源起到了一定作用,但治理绩效的影响仍未得到充分研究。本研究通过将治理指标与疫情应对数据相结合,以评估治理质量(独立于收入水平)如何影响国家结果,填补了这一重大空白。尽管牛津新冠政府应对追踪器(OxCGRT)数据集已被广泛用于记录政策应对措施,但本研究通过将这些政策干预与治理绩效联系起来,并评估它们对健康结果和疫苗公平性的联合影响,做出了新颖的贡献。

方法

这项混合方法研究将全球数据集的定量分析与定性文献综述相结合。定量数据主要来自牛津新冠政府应对追踪器(OxCGRT)、世界银行的全球治理指标(WGI)以及世界银行/世卫组织数据库。使用两个WGI组成部分构建了治理绩效指数:政府效能和监管质量。国家被分为高、中、低治理类别。统计测试包括方差分析、卡普兰 - 迈耶生存分析和多变量OLS回归。定性部分回顾了45篇关于新冠疫情期间治理绩效的学术和机构资料。

结果

治理绩效高的国家在公共卫生干预方面更早,死亡率更低,疫苗覆盖范围更广,且与收入水平无关。卡普兰 - 迈耶分析显示这些国家学校关闭速度更快(<0.01)。多变量回归表明,在调整收入和卫生支出后,治理仍然是一个重要的预测因素。定性研究结果突出了法律可执行性、政府间协调和全球融资机制中反复出现的弱点。

结论

治理绩效对疫情结果具有决定性影响。新冠危机表明需要强大的治理体系,能够应对超越卫生部门,延伸到机构、经济和社会领域的复杂紧急情况。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/561c/12386743/9efc0eb64044/ijerph-22-01305-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/561c/12386743/ea2edb733d5a/ijerph-22-01305-g0A1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/561c/12386743/a72d65217d31/ijerph-22-01305-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/561c/12386743/0ed046e584df/ijerph-22-01305-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/561c/12386743/73589b7090f6/ijerph-22-01305-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/561c/12386743/a87ace4f0f3c/ijerph-22-01305-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/561c/12386743/35c38dd0db95/ijerph-22-01305-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/561c/12386743/9efc0eb64044/ijerph-22-01305-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/561c/12386743/ea2edb733d5a/ijerph-22-01305-g0A1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/561c/12386743/a72d65217d31/ijerph-22-01305-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/561c/12386743/0ed046e584df/ijerph-22-01305-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/561c/12386743/73589b7090f6/ijerph-22-01305-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/561c/12386743/a87ace4f0f3c/ijerph-22-01305-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/561c/12386743/35c38dd0db95/ijerph-22-01305-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/561c/12386743/9efc0eb64044/ijerph-22-01305-g006.jpg

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