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援助核算:运用合成控制法和贝叶斯方法评估美国全球卫生投资对育龄妇女死亡率的影响

Accounting for aid: estimating the impact of United States' global health investments on mortality among women of reproductive age using synthetic control and Bayesian methods.

作者信息

Ahsan Karar Zunaid, Angeles Gustavo, Choudhury Allysha, Singh Kavita, Taylor Tory M, Majid Farhan, Lucas Rachel, Cohen Robert L, Gawande Atul A, Weiss William

机构信息

Department of Public Health Leadership and Practice, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.

Data for Impact (D4I), Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.

出版信息

J Glob Health. 2025 Mar 21;15:04067. doi: 10.7189/jogh.15.04067.

DOI:10.7189/jogh.15.04067
PMID:40116331
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11927036/
Abstract

BACKGROUND

The United States government (USG) is a key global actor in preventing mortality and supporting lifesaving health services among women and children in low- and middle-income countries (LMICs). Since the Foreign Assistance Act of 1961, USG has funded global health programmes targeting specific conditions and strengthening health systems for the delivery of essential services via the United States Agency for International Development (USAID) and other USG agencies. However, directly quantifying and attributing the impact of USG health investments is challenging due to the inability of conducting randomised control trials for such large programmes at scale. In this study, we compared two quasi-experimental impact evaluation approaches to estimate the effects of sustained USG health investments on mortality among women of reproductive age (WRA).

METHODS

We employed synthetic control analysis and a Bayesian alternative to synthetic control to estimate the impact of USG's global health investments on WRA mortality rate across 16 LMICs that received sustained, multifaceted, and above-average USAID global health funding levels from 2005 to 2019.

RESULTS

Countries receiving sustained, multifaceted, and above-average USAID global health funding had a reduction in the annual WRA mortality rate by 0.65 deaths per 1000 WRA throughout the post-treatment period. For the years (i.e. 2009-2019) where the effect estimates are statistically significant (P < 0.001), the reduction in WRA mortality rate was 0.80 deaths per 1000 WRA. Sensitivity analyses and Bayesian modelling supported the robustness of these findings. We conservatively estimated that about 1.0-1.3 million WRA deaths were averted in study countries between 2009 and 2019 as a result of USG health investments.

CONCLUSIONS

Our results suggest that well-funded donor initiatives can substantially reduce WRA mortality rates beyond what would have been achieved without such investments. Sustained donor investments significantly reduce WRA mortality, underscoring the transformative potential of well-funded global health initiatives. Our study also demonstrates that synthetic control and Bayesian models are valuable tools for evaluating the impact of large-scale global health financing.

摘要

背景

美国政府(USG)是全球预防中低收入国家(LMICs)妇女和儿童死亡及支持救生健康服务的关键行为体。自1961年《对外援助法》以来,美国政府通过美国国际开发署(USAID)和其他美国政府机构,为针对特定疾病的全球卫生项目提供资金,并加强卫生系统以提供基本服务。然而,由于无法大规模开展此类大型项目的随机对照试验,直接量化和归因美国政府卫生投资的影响具有挑战性。在本研究中,我们比较了两种准实验性影响评估方法,以估计美国政府持续的卫生投资对育龄妇女(WRA)死亡率的影响。

方法

我们采用合成控制分析和合成控制的贝叶斯替代方法,来估计美国政府全球卫生投资对2005年至2019年期间接受美国国际开发署持续、多方面且高于平均水平全球卫生资金的16个中低收入国家育龄妇女死亡率的影响。

结果

在整个治疗后期间,接受持续、多方面且高于平均水平美国国际开发署全球卫生资金的国家,育龄妇女年死亡率每1000名育龄妇女降低了0.65例死亡。在效应估计具有统计学意义(P < 0.001)的年份(即2009 - 2019年),育龄妇女死亡率的降低为每1000名育龄妇女0.80例死亡。敏感性分析和贝叶斯建模支持了这些结果的稳健性。我们保守估计,2009年至2019年期间,由于美国政府的卫生投资,研究国家避免了约100万至130万例育龄妇女死亡。

结论

我们的结果表明,资金充足的捐助方倡议可以大幅降低育龄妇女死亡率,超出没有此类投资时所能达到的水平。持续的捐助方投资显著降低了育龄妇女死亡率,凸显了资金充足的全球卫生倡议的变革潜力。我们的研究还表明,合成控制和贝叶斯模型是评估大规模全球卫生融资影响的宝贵工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce83/11927036/b7430759b90e/jogh-15-04067-F3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce83/11927036/034b487c12d1/jogh-15-04067-F1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce83/11927036/4cc5ef755eb8/jogh-15-04067-F2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce83/11927036/b7430759b90e/jogh-15-04067-F3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce83/11927036/034b487c12d1/jogh-15-04067-F1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce83/11927036/4cc5ef755eb8/jogh-15-04067-F2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ce83/11927036/b7430759b90e/jogh-15-04067-F3.jpg

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