AI RESEARCH
EpiQAL: Benchmarking Large Language Models in Epidemiological Question Answering and Reasoning
arXiv CS.AI
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ArXi:2601.03471v3 Announce Type: replace-cross Reliable epidemiological reasoning requires synthesizing study evidence to infer disease burden, transmission dynamics, and intervention effects at the population level. Existing medical question answering benchmarks primarily emphasize clinical knowledge or patient-level reasoning, yet few systematically evaluate evidence-grounded epidemiological inference. We present EpiQAL, the first diagnostic benchmark for epidemiological question answering across diverse diseases, comprising three subsets built from open-access literature.