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通过综合全球卫生安全指数(GHSI)、多准则决策方法(MCDM)和聚类模型对西亚卫生安全进行基于收入的分析。

Income-Based analysis of health security in Western Asia through an integrated GHSI, MCDM, and Clustering Model.

作者信息

Nasser Adel A, Alghawli Abed Saif Ahmed, Saleh Salem, Elsayed Amani A K

机构信息

Department of Artificial Intelligence,, Modern Specialized University, Sana'a, Yemen.

Department of Information Systems and Computer Science, Sa'adah University, Sa'adah University, Sa'adah, Yemen.

出版信息

F1000Res. 2025 Mar 28;14:43. doi: 10.12688/f1000research.159002.1. eCollection 2025.

DOI:10.12688/f1000research.159002.1
PMID:40115665
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11923535/
Abstract

OBJECTIVES

Infectious diseases present significant challenges to global health security in contemporary, interconnected global environments. This study aimed to evaluate and compare health security performance in Western Asia (WA), with a focus on income group-based disparities and region-specific insights.

METHODS

This study utilized the Global Health Security Index (GHSI) to assess health security across 17 WA countries categorized by income level. Health security indicators for 2019 and 2021 were analyzed using the D-CRITIC method to determine the relative importance of each indicator (Global Health Security Index, 2021): https://ghsindex.org/report-model/). A combined D-CRITIC-CoCoSo framework was employed to rank the countries, followed by K-means clustering for grading. The study also investigated correlations between financial allocation's indicators and health security outcomes using Spearman's rank correlation. A comparative analysis elucidated regional disparities across income categories.

RESULTS

This study highlights WA's progress in health security by prioritizing foundational health systems, detection/reporting, rapid response, and risk management. From 2019 to 2021, priorities varied by income group, with high-income countries focusing on detection, upper-middle-income countries focusing on risk environments, and low-income countries focusing on prevention. While some nations demonstrated improvement, others, such as Armenia, experienced decline, revealing persistent vulnerabilities. This study revealed significant variability in health security capacity, with both progress and setbacks among countries in different clusters. High- and upper-middle-income countries, such as Qatar and Georgia, leverage investments and international partnerships to improve their rankings, while conflict-affected, low-resource countries, including Iraq, Yemen, and Syria, face stagnation or decline. Strong correlations were observed between financial resource allocation indicators and health performance. Higher investments in countries like Armenia and Georgia led to significantly improved health outcomes, while minimal spending in Syria and Yemen weakened their resilience to health threats.

CONCLUSION

Disparities in health resilience persist, underscoring the need for equitable resource allocation and regional cooperation to enhance public health security.

摘要

目标

在当代相互关联的全球环境中,传染病对全球卫生安全构成重大挑战。本研究旨在评估和比较西亚(WA)的卫生安全绩效,重点关注基于收入群体的差异以及特定区域的见解。

方法

本研究利用全球卫生安全指数(GHSI)评估17个按收入水平分类的西亚国家的卫生安全情况。使用D - CRITIC方法分析2019年和2021年的卫生安全指标,以确定每个指标的相对重要性(《全球卫生安全指数,2021》:https://ghsindex.org/report - model/)。采用组合的D - CRITIC - CoCoSo框架对各国进行排名,随后使用K - 均值聚类进行分级。该研究还使用斯皮尔曼等级相关性研究了财政拨款指标与卫生安全结果之间的相关性。比较分析阐明了不同收入类别的区域差异。

结果

本研究强调了西亚在卫生安全方面通过优先考虑基础卫生系统、检测/报告、快速反应和风险管理取得的进展。从2019年到2021年,优先事项因收入群体而异,高收入国家侧重于检测,中高收入国家侧重于风险环境,低收入国家侧重于预防。虽然一些国家有所改善,但其他国家,如亚美尼亚,却出现了下降,这表明存在持续的脆弱性。本研究揭示了卫生安全能力的显著差异,不同集群中的国家既有进展也有挫折。卡塔尔和格鲁吉亚等高收入和中高收入国家利用投资和国际伙伴关系来提高其排名,而受冲突影响、资源匮乏的国家,包括伊拉克、也门和叙利亚,则面临停滞或下降。在财政资源分配指标与卫生绩效之间观察到了强相关性。亚美尼亚和格鲁吉亚等国的更高投资导致卫生结果显著改善,而叙利亚和也门的极少支出削弱了它们对卫生威胁的抵御能力。

结论

卫生恢复力的差异依然存在,这突出表明需要公平分配资源并开展区域合作,以加强公共卫生安全。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94d6/11953614/b15f5907a2e8/f1000research-14-179587-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94d6/11953614/38e7c4a989e7/f1000research-14-179587-g0000.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94d6/11953614/42708e0ed92f/f1000research-14-179587-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94d6/11953614/b15f5907a2e8/f1000research-14-179587-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94d6/11953614/38e7c4a989e7/f1000research-14-179587-g0000.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94d6/11953614/42708e0ed92f/f1000research-14-179587-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/94d6/11953614/b15f5907a2e8/f1000research-14-179587-g0002.jpg

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