Artificial intelligence and infodemic management: a governance framework for public health

Abstract

Background: Digital communication ecosystems have amplified the spread of health misinformation, creating infodemics that challenge public health systems. While artificial intelligence (AI) enables real-time monitoring of information dynamics, its integration into public health decision-making remains limited.

Methods: An evidence-informed conceptual framework was developed building on a previously conducted scoping review of studies investigating AI and digital technologies for infodemic management. An interpretive evidence synthesis approach was used to identify key functional domains and translate them into a governance-oriented model.

Results: The synthesis of 63 studies identified core domains of digital infodemic management, including digital monitoring and infoveillance, AI-based misinformation detection, infodemic dynamics in digital ecosystems, communication strategies, and governance frameworks. Building on these domains, a four-component governance framework was developed, integrating digital data ecosystems, AI analytics, interpretive public health expertise, and institutional decision-making processes. The model describes a structured pathway through which digital signals are transformed into coordinated public health responses.

Conclusions: AI provides powerful tools for monitoring complex digital information environments, but effective public health impact depends on governance structures capable of translating analytical insights into coordinated action. This framework offers a structured model to support decision-making in digital public health systems.

Key messages: • Artificial intelligence and infodemic management: a governance framework for Public Health.

• Integrating AI analytics with governance frameworks enables the translation of digital insights into effective public health action.

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Cite

BibTeX RIS

BibTeX

@article{cianciulli2026artificial,
  title = {{Artificial intelligence and infodemic management: a governance framework for public health}},
  author = {A Cianciulli and E Santoro and A Pacifico and E Nuccio and A Armenante and M Finizio and G Comunale and N Marra and SQ Quagliarella and G Boccia},
  journal = {The European Journal of Public Health},
  year = {2026},
  month = oct,
  doi = {10.1093/eurpub/ckag169.1210},
  url = {https://doi.org/10.1093/eurpub/ckag169.1210},
  note = {CC BY-NC 4.0},
}

RIS

TY  - JOUR
TI  - Artificial intelligence and infodemic management: a governance framework for public health
AU  - A Cianciulli
AU  - E Santoro
AU  - A Pacifico
AU  - E Nuccio
AU  - A Armenante
AU  - M Finizio
AU  - G Comunale
AU  - N Marra
AU  - SQ Quagliarella
AU  - G Boccia
PY  - 2026
DA  - 2026/10/01
JO  - The European Journal of Public Health
DO  - 10.1093/eurpub/ckag169.1210
UR  - https://doi.org/10.1093/eurpub/ckag169.1210
AB  - Background: Digital communication ecosystems have amplified the spread of health misinformation, creating infodemics that challenge public health systems. While artificial intelligence (AI) enables real-time monitoring of information dynamics, its integration into public health decision-making remains limited.  Methods: An evidence-informed conceptual framework was developed building on a previously conducted scoping review of studies investigating AI and digital technologies for infodemic management. An interpretive evidence synthesis approach was used to identify key functional domains and translate them into a governance-oriented model.  Results: The synthesis of 63 studies identified core domains of digital infodemic management, including digital monitoring and infoveillance, AI-based misinformation detection, infodemic dynamics in digital ecosystems, communication strategies, and governance frameworks. Building on these domains, a four-component governance framework was developed, integrating digital data ecosystems, AI analytics, interpretive public health expertise, and institutional decision-making processes. The model describes a structured pathway through which digital signals are transformed into coordinated public health responses.  Conclusions: AI provides powerful tools for monitoring complex digital information environments, but effective public health impact depends on governance structures capable of translating analytical insights into coordinated action. This framework offers a structured model to support decision-making in digital public health systems.  Key messages: • Artificial intelligence and infodemic management: a governance framework for Public Health.  • Integrating AI analytics with governance frameworks enables the translation of digital insights into effective public health action.
SN  - 1101-1262
SN  - 1464-360X
ER  -

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