An Infectious Disease Spread Simulation Based on Large Language Model Decision Making
Modelling individual decision-making during infectious disease outbreaks is crucial for understanding behavioural dynamics and informing effective public health interventions. Prior work has shown that large language models can simulate realistic human behaviour by generating agent decisions based on demographic prompts and situational context. We build on this foundation with a spatially grounded, agent-based simulation framework that integrates LLM-generated decisions about self-reported influenza-like illness into a census-based synthetic population of agents. Location is treated as a central feature: agents are assigned to spatial units within cities, capturing the spatial distributio...
| Authors | Yonchanok Khaokaew, Ruochen Kong, Andreas Zufle et al. |
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| Primary category | cs.AI |
| Published | 4 June 2026 |
| Last updated at source | 8 June 2026 |
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