Artificial intelligence in public health: the potential of epidemic early warning systems

Abstract

The use of artificial intelligence (AI) to generate automated early warnings in epidemic surveillance by harnessing vast open-source data with minimal human intervention has the potential to be both revolutionary and highly sustainable. AI can overcome the challenges faced by weak health systems by detecting epidemic signals much earlier than traditional surveillance. AI-based digital surveillance is an adjunct to—not a replacement of—traditional surveillance and can trigger early investigation, diagnostics and responses at the regional level. This narrative review focuses on the role of AI in epidemic surveillance and summarises several current epidemic intelligence systems including ProMED-mail, HealthMap, Epidemic Intelligence from Open Sources, BlueDot, Metabiota, the Global Biosurveillance Portal, Epitweetr and EPIWATCH. Not all of these systems are AI-based, and some are only accessible to paid users. Most systems have large volumes of unfiltered data; only a few can sort and filter data to provide users with curated intelligence. However, uptake of these systems by public health authorities, who have been slower to embrace AI than their clinical counterparts, is low. The widespread adoption of digital open-source surveillance and AI technology is needed for the prevention of serious epidemics.

Artificial Intelligence in battling infectious diseases: A transformative role

“…AI-based digital disease surveillance systems have demonstrated their effectiveness in forecasting infectious disease outbreaks. 27,30,31 However, to improve their efficacy, these systems require continual optimization and extensive learning to guarantee prompt and accurate early warningsa crucial element for swift human responses to infectious disease outbreaks.…”

Respiratory illness of unknown cause as an early signal of the COVID-19 pandemic

“…EPIWATCH is an AI-driven disease surveillance system that harnesses open-source data to monitor EIDs [25]. EPIWATCH scans daily media articles and other Internet sources using two AI systems and prespecified search terms in 42 different languages (at the time of this study) for clinical syndromes and specific diseases worldwide [25], enabling rapid detection of early outbreak signals.…”

AI: the future of humanity

“…AI-based techniques for early diagnosis and control of infectious diseases are critical in preventing outbreaks from spreading. AI algorithms may evaluate a wide range of data sources, including social media, medical records, and mobility patterns, to detect early indicators of disease outbreaks and pinpoint high-risk locations for targeted interventions [39]. Furthermore, AI-driven vaccine development and distribution strategies can speed up the vaccine discovery process and optimize vaccine distribution based on parameters such as population density and vulnerability.…”