Optimal allocation of antenatal and young child nutrition interventions: an individual-based global burden of disease calibrated microsimulation.

Background: Undernutrition remains a global crisis and is a focus of Sustainable Development Goals. While there are multiple known, effective interventions, complex interactions between prevention and treatment and resource constraints can lead to difficulties in allocating funding. Simulation studies that use in silico simulation can help illuminate the interactions between interventions and provide insight into the cost-effectiveness of alternative packages of options.

Methods: We developed an individual-based microsimulation model based on the Global Burden of Disease (GBD) 2021 study data to test a range of nutrition interventions, including antenatal interventions (iron and folic acid, multiple micronutrients, and balanced energy protein supplementation) and child interventions (treatment for severe acute malnutrition, treatment for moderate acute malnutrition, and wasting prevention with small-quantity lipid-based nutrient supplements). We also developed an analytic approach to process the results of the microsimulation and identify the optimal intervention funding allocation for a given budget size. We use Ethiopia as an example in this paper.

Results: In our illustrative example of Ethiopia, the reallocation of the baseline budget to minimize disability-adjusted life years (DALYs) resulted in first funding the antenatal multiple micronutrients to their maximum coverage and then funding treatment for severe child acute malnutrition. Relative to the baseline allocation, the reallocation optimized to minimizing DALYs resulted in 592,000 fewer annual DALYs, constituting an 8.3% reduction in total DALYs in Ethiopia. For budgets larger than the baseline, our model recommended funding first targeted moderate acute malnutrition treatment, second universal moderate acute malnutrition treatment, third wasting prevention with small-quantity lipid-based nutrient supplements, and fourth balanced energy protein supplementation.

Conclusions: Our simulation is a novel model for estimating optimal allocation of spending on antenatal and child health nutrition interventions which accounts for the interaction between preventive and therapeutic approaches. Our illustrative results show that an optimized reallocation of current spending can substantially improve pregnancy-related and child health without additional funding. We hope this model can add validity and confidence to prior results to aid stakeholders in funding decisions.