# Digital twin simulations of theory-driven crisis messaging during hurricane evacuations in synthetic populations: a Miami-Dade County case study

## TL;DR

This study uses digital twin simulations to test how different crisis messages affect evacuation decisions during hurricanes in Miami-Dade County.

## Contribution

It introduces a Message Assessment Framework and demonstrates how agentic AI and digital twins can pre-test emergency communication strategies.

## Key findings

- Messages combining fear and efficacy were most effective in encouraging evacuation (OR = 15.45, p < 0.001).
- Adding social cues to messages did not significantly improve their effectiveness.
- Digital twin simulations offer a scalable method to optimize emergency messaging before real-world use.

## Abstract

Digital twin and agentic artificial intelligence technology provide innovative systems for testing behavioral science theory, which can improve emergency communication in crisis situations. More advanced and effective evidence-based messaging is needed for better safety preparation for extreme weather and more trusted evacuation communication.

This study developed a digital twin of Miami-Dade County populated with a synthetic population embedded with behavioral theory (Extended Parallel Process Model, Theory of Planned Behavior) and the development of a Message Assessment Framework (MAF) to systematically test theory-based crisis messages. Agents were exposed to fear-only, efficacy-only, norm-only, combined fear+efficacy, combined fear+efficacy+norm, and a neutral control message.

Messages grounded in behavioral theory were more effective than the control message at encouraging evacuation. Messages that combined fear and efficacy provided the best results in the synthetic population’s decision to evacuate (OR = 15.45, p < 0.001), while adding social cues did not produce a statistically distinguishable added benefit.

This research demonstrates a proof-of-concept approach for using agentic AI and digital twins to pre-test communication strategies, offering a scalable method for optimizing emergency messaging prior to real-world implementation.