Dynamic copula Bayesian network predictive model for assessing the impact of initiative programs on child undernutrition in Ethiopia, 2009–2016

The study demonstrates the utility of DCBNs for mapping dynamic, nonlinear associations between social protection and health programs and child undernutrition determinants. The results highlight that strengthening household food security and wealth plays a central role in reducing child undernutrition. Although findings are associational, the transferable dependence map can be re-estimated with contemporary data to guide program targeting, monitoring, and policy decisions in Ethiopia.