Background Inequalities in the health and non-health benefits of public health interventions are a key challenge on the path to universal health coverage, particularly in LMICs. The design of HBP creates an opportunity in selecting interventions through established criteria. A quantitative analytic method was employed for integrating the distributional health and financial protection impact during the prioritization of interventions.
Methods Data on average health benefits, costs, disease prevalence, and population size were extracted from the GBD and latest Ethiopian essential health service package (EHSP) database, survey, and published sources. Benefits were distributed across quintiles using a combined adjusted risk of disease prevalence and coverage, with the latter used to distribute total costs. For each intervention (30 in total), a 95% target coverage (applied to current coverage vs. to the gap in coverage across quintile) was analyzed. Inequality and social welfare indices, and financial protection metrics were estimated.
Results Twenty-four interventions were found to improve population health and reduce health inequality, 4 interventions to reduce population health and increase health inequality, and 2 interventions to improve population health and increase health inequality. In the case of the latter two, social welfare analysis using inequality aversion parameters (Ꜫ=10) revealed that the health benefit outweighs the negative impact of health inequality.
Overall, the selected EHSP interventions provide 0.021 HALE per person in Ethiopia, with 0.034 (32% in the poorest) and 0.01 (9%) HALE gained in the richest. Similarly, a total of 76, 726 cases of CHE were averted, with 46,123 cases in the poorest and 15,151 cases in the richest.
Conclusion We found that improving access to the EHSP by reaching the uncovered population groups across each income group improves health equity; however, adding incremental coverage to existing coverage amplifies the existing health inequality more.
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