The Impact of Heatwaves on Population Health: A Large Language Model-Enhanced Agent-Based Simulation
Yuanhao Liu, Yuanfei Liu, Tian Lu, Hengyang Zhang, Zuowei Wang, and Ying Dai

TL;DR
This study employs a Large Language Model-enhanced agent-based simulation to explore how community resilience to heatwaves varies with vulnerability, revealing psychosocial impacts and social information diffusion patterns.
Contribution
It introduces a novel LLM-enhanced agent-based model to simulate behavioral responses and social dynamics during heatwaves, advancing understanding of resilience mechanisms.
Findings
Higher vulnerability correlates with larger declines in perceived safety and social connection.
Resilient agents maintain protective behaviors, while vulnerable agents show behavioral constriction.
Risk information spreads through social reinforcement, not just broad exposure.
Abstract
Extreme heat events are increasing in frequency and intensity under climate change, but the socio-behavioral mechanisms that shape community resilience remain insufficiently understood. This study uses a Large Language Model-enhanced agent-based model to simulate responses to a prolonged heatwave in a virtual society. One hundred heterogeneous agents were assigned a Heat Vulnerability Index based on demographic risk factors and observed over 13 simulated days covering baseline, heatwave, and recovery periods. The simulation shows that heat-related impacts are primarily psychosocial and unequally distributed. Agents with higher vulnerability experienced larger declines in perceived safety and social connection than agents with lower vulnerability. Vulnerability also shaped adaptive capacity. More resilient agents maintained routine self-care and protective behaviors, whereas highly…
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