Constrained optimization: evaluating possible packages of community health interventions with competing resource requirements in Galmudug, Somalia.

Abstract

Investment in Community Health Worker (CHW) programs has allowed health systems to reach previously underserved rural and remote populations. As a result, CHWs are often burdened with responsibilities to deliver large packages of services, at times without sufficient human, financial, or health resources. To design a community-level program that saves maternal and newborn lives while operating within resource limitations, we used constrained optimization (a mathematical process for finding the solution to a stated objective while accounting for listed requirements) to construct a model for select villages in Galmudug State, Somalia. After establishing the resource requirements for delivering 25 evidence-based maternal and neonatal interventions, we used the Lives Saved Tool (LiST) and optimization techniques to determine the package of care that leads to the most projected lives saved. With a cadre of 1,450 Female Health Workers and a budget of $435,000 for maternal and neonatal health commodities and programming over one year, we calculated that the optimized set of interventions for Galmudug could avert 15% of the 4,132 projected maternal and neonatal deaths in 2024. We also conducted sensitivity analyses to show how the optimal combination of interventions and the number of lives saved change as the resource levels change. The model provides practitioners with a new tool and accompanying approach to evaluate possible packages of community health interventions with competing resource requirements.