  This study offers a new paradigm of individual-level modeling to address the
grand challenge of incorporating human behavior in epidemic models. Using
generative artificial intelligence in an agent-based epidemic model, each agent
is empowered to make its own reasonings and decisions via connecting to a large
language model such as ChatGPT. Through various simulation experiments, we
present compelling evidence that generative agents mimic real-world behaviors
such as quarantining when sick and self-isolation when cases rise.
Collectively, the agents demonstrate patterns akin to multiple waves observed
in recent pandemics followed by an endemic period. Moreover, the agents
successfully flatten the epidemic curve. This study creates potential to
improve dynamic system modeling by offering a way to represent human brain,
reasoning, and decision making.
