Adversarial Data Modeling in Epidemiology
Read the original on arXiv AI →The paper introduces a signaling‑game framework to model how individuals strategically misreport behavioral data—such as mask usage and vaccination status—to public health authorities. It provides a generative model of such adversarial data and a method for authorities to recover reliable signals, analyzing equilibrium outcomes and evaluating how deception affects epidemic control. Large‑scale simulations and real‑world validation show that well‑designed sender and receiver strategies can still maintain effective epidemic control even with pervasive dishonesty, and that behavioral distortions often follow structured patterns rather than random noise.
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