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

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.