Researchsignal detectionpublic healthhorizon scanning
AI Enhances Horizon Scanning For Infectious Diseases
7.0
Valdir Ermida reviews integration of Artificial Intelligence into horizon scanning for infectious diseases in a paper submitted 3 December 2025, examining signal detection, data monitoring, scenario analysis, and decision support. The review details risks such as bias and data-quality issues, proposes governance and implementation strategies, and situates findings within foresight literature for public-health preparedness.
Key Points
- 1Demonstrates AI-enabled signal detection improves early identification of infectious disease threats across diverse data streams
- 2Highlights governance, bias, and data-quality risks that could undermine surveillance accuracy and public trust
- 3Recommends integrating AI with scenario analysis and decision support to inform preparedness and response planning
Scoring Rationale
Synthesis of AI methods for public-health horizon scanning; useful strategic guidance but limited by single-review evidence without empirical deployment
Sources
Public references used for this report.
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