Comparison of verbal autopsy using a large language model to biologically confirmed causes of death for malaria and other communicable diseases among children in six sub-Saharan African countries

GPT-4o demonstrated superior performance over probabilistic VA models in identifying malaria-attributed deaths. National vital registration authorities and health ministries should consider integrating large language model-driven tools into their VA systems to enhance diagnostic precision. While less practicable at scale, focal and periodic MITS comparisons are useful for improving verbal autopsy systems. National mortality data are essential to track progress in reducing childhood deaths from malaria and other conditions.