Estimating the impact of donor programs on child mortality in low- and middle-income countries: a synthetic control analysis of child health programs funded by the United States Agency for International Development

Abstract

Background Significant levels of funding have been provided to low- and middle-income countries for development assistance for health, with most funds coming through direct bilateral investment led by the USA and the UK. Direct attribution of impact to large-scale programs funded by donors remains elusive due the difficulty of knowing what would have happened without those programs, and the lack of detailed contextual information to support causal interpretation of changes. Methods This study uses the synthetic control analysis method to estimate the impact of one donor’s funding (United States Agency for International Development, USAID) on under-five mortality across several low- and middle-income countries that received above average levels of USAID funding for maternal and child health programs between 2000 and 2016. Results In the study period (2000–16), countries with above average USAID funding had an under-five mortality rate lower than the synthetic control by an average of 29 deaths per 1000 live births (year-to-year range of − 2 to − 38). This finding was consistent with several sensitivity analyses. Conclusions The synthetic control method is a valuable addition to the range of approaches for quantifying the impact of large-scale health programs in low- and middle-income countries. The findings suggest that adequately funded donor programs (in this case USAID) help countries to reduce child mortality to significantly lower rates than would have occurred without those investments.

Evaluating Country Performance After Transitioning From Gavi Assistance: An Applied Synthetic Control Analysis

“…[7][8][9][10] Synthetic control has been used to assess governance on progress toward universal health coverage and health outcomes, as well as to estimate the impact of donor programs on child mortality in low-and middle-income countries. [47][48][49] We computed the statistical significance of the counterfactual public health outcomes in the hypothetical absence of the phased transition from Gavi assistance by estimating the same outcome-linked model specification on each unaffected country and obtained the distribution of placebo effects by iteratively shifting the treated country in the donor pool. Supplement 2 provides a more detailed technical methodological description.…”