Work

A BEACON for Novel Disease Threats: Leveraging Artificial Intelligence for Informal Event-Based Outbreak Surveillance

Year: 2025

Type: article

Abstract: Event-based surveillance systems have proven critical for early detection of disease outbreaks by analyzing informal data sources, and the integration of artificial intelligence (AI) offers new opportunities to enhance these capabilities at scale. We describe the Biothreats Emergence, Analysis and Communications Network (BEACON), a novel platform that combines a domain-adapted large language model with expert human oversight to provide rapid, contextualized outbreak reporting across the globe, while highlighting both the transformative potential and current limitations of AI-assisted disease surveillance.

Source: The Journal of Infectious Diseases

DOI: 10.1093/infdis/jiaf642

Authors: Nahid Bhadelia, Ioannis Ch Paschalidis, John S Brownstein, Britta Lassman

Institutions: Boston University, Boston Children's Hospital, Harvard University

Language: English

Topic: Data-Driven Disease Surveillance

Subfield: Epidemiology

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: hybrid

Estimated APC paid: $4,763