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EPIWATCH, an artificial intelligence early-warning system as a valuable outbreak surveillance tool
Conference presentation

EPIWATCH, an artificial intelligence early-warning system as a valuable outbreak surveillance tool

Ashley Quigley, Damian Honeyman, Haley Stone, Rebecca Dawson and Raina MacIntyre Professor
Communicable Diseases & Immunisation Conference 2025 (CDIC) (Adelaide, Australia, 10/06/2025–12/06/2025)
Communicable Diseases & Immunisation Conference 2025 (CDIC) (Adelaide, Australia, 10/06/2025–12/06/2025)
11/06/2025

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Abstract

Artificial intelligence (AI) presents a transformative approach to public health surveillance, particularly in environments where traditional methods are limited or absent. By leveraging opensource data, AI-driven systems can provide epidemic intelligence, offering early warning signals of infectious disease outbreaks. EPIWATCH is an AI-powered outbreak detection and monitoring system that has demonstrated the ability to identify epidemic signals before official detection by health authorities. This study evaluates the utility of open-source epidemic intelligence through two case studies. EPIWATCH reports on outbreaks of unspecified influenza-like illness and pneumonia- along with known causes such as influenza A/B, SARS-CoV-2, RSV, pertussis, adenovirus, and Mycoplasma pneumoniae from August to December of 2022 and 2023 were analyzed. In China, EPIWATCH detected an increase in respiratory illness in 2023 compared to 2022, contrasting with a global decline during the same period. Notably, a peak in pneumonia cases was identified from October to early November 2023, preceding the official recognition of Mycoplasma pneumoniae outbreaks by the WHO on 22 November 2023. To assess EPIWATCH’s utility in conflict zones, we analyzed infectious disease patterns in Ukraine before (November 2021–February 2022) and during the conflict (February–July 2022). Comparison with official sources revealed increased infectious disease reports during wartime, highlighting the system’s potential for real-time epidemic intelligence in crisis settings. These findings highlight the power of AI-driven surveillance in early outbreak detection, particularly in resource-constrained and conflict-affected regions. By complementing traditional surveillance, AI systems like EPIWATCH can optimize response and preparedness efforts, ultimately improving global health security. Given the acceleration of epidemics in recent years, leveraging open-source intelligence for rapid outbreak detection is essential for timely intervention.

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