Improving Crisis Communication through Translation: A Study of U.S. Emergency Response and Disaster Management Contexts

Abstract

This study, Improving Crisis Communication through Translation: A Study of United States Emergency Response and Disaster Management Contexts, examines how human and artificial intelligence-assisted translation improve clarity, timeliness, and trust in crisis communication. A mixed-methods approach incorporating quantitative, qualitative, and computational analysis was employed to analyze 320 multilingual emergency alerts disseminated by the Federal Emergency Management Agency, the Centers for Disease Control and Prevention, and the American Red Cross. Supplementary data was obtained from twelve institutional policy reports and a field experiment with 240 participants, comprising emergency officials, translators, and multilingual people from English, Spanish, Arabic, and Mandarin communities. The findings indicate that translation significantly enhanced comprehension—from 62.4 to 87.1 percent—while decreasing message delays and bolstering public trust. Human translators exhibited superior contextual and semantic precision, while hybrid human-machine systems provided the optimal equilibrium of quality and efficiency. Translated notifications exhibited enhanced clarity and accessibility, with translation duration diminished from 7.8 to 2.4 hours and multilingual availability attaining 75.8 percent. The study offers two significant contributions: the Translation Responsiveness Model, which correlates translation performance with clarity, timeliness, and trust; and the Institutional Translation Maturity Index, a framework for assessing the incorporation of translation in emergency management. Translation is considered an essential operational role crucial for equity, credibility, and public safety.