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Review
. 2023 Mar;51(3):3000605231159335.
doi: 10.1177/03000605231159335.

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

Chandini Raina MacIntyre  1   2 , Xin Chen  1 , Mohana Kunasekaran  1 , Ashley Quigley  1 , Samsung Lim  1   3 , Haley Stone  1 , Hye-Young Paik  4 , Lina Yao  4 , David Heslop  5 , Wenzhao Wei  1 , Ines Sarmiento  1 , Deepti Gurdasani  6
Affiliations
Review

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

Chandini Raina MacIntyre et al. J Int Med Res. 2023 Mar.

Erratum in

  • Corrigendum.
    [No authors listed] [No authors listed] J Int Med Res. 2023 May;51(5):3000605231178098. doi: 10.1177/03000605231178098. J Int Med Res. 2023. PMID: 37195890 Free PMC article. No abstract available.

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.

Keywords: Artificial intelligence; digital surveillance; early warning system; epidemic intelligence; pandemic; public health.

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Conflict of interest statement

The authors declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: The authors are part of the EPIWATCH system.

Figures

Figure 1.
Figure 1.
Enhancement of epidemic detection by rapid epidemic intelligence and risk analysis.
See this image and copyright information in PMC

References

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