Antimalarial Pharmacotherapy Gaps in Nigerian Children Under Five: A Predictive Machine Learning Analysis of Care-Seeking, Testing, and ACT Treatment Using NDHS 2023-24
This study utilizing 2023-24 NDHS data and four machine learning models reveals that household and maternal characteristics poorly predict antimalarial care gaps in Nigerian children under five, though financial barriers consistently emerge as a significant determinant of suboptimal ACT treatment, suggesting cost reduction at the point of sale as a key intervention target.