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Area of Science:

  • Public health
  • Communication science
  • Artificial intelligence

Background:

  • Vaccination communication aims to reduce vaccine hesitancy and identify high-risk communities.
  • Artificial intelligence (AI) tools are proposed for surveillance and intervention design.
  • Limited evidence exists on AI implementation in public health practice.

Purpose of the Study:

  • To examine proposed AI applications in vaccine surveillance and communication interventions.
  • To discuss barriers hindering AI implementation in public health.
  • To recommend strategies for overcoming barriers and mitigating unintended consequences.

Main Methods:

  • Review of recent advances in AI for public health surveillance.
  • Analysis of AI applications in designing communication interventions.
  • Exploration of implementation challenges and potential solutions.

Main Results:

  • AI offers potential for targeted vaccine hesitancy interventions and surveillance.
  • Significant barriers impede the practical implementation of AI in public health.
  • Strategies are needed to facilitate AI adoption and prevent negative outcomes.

Conclusions:

  • AI presents opportunities to enhance vaccine communication and surveillance efforts.
  • Addressing implementation barriers is crucial for realizing AI's public health potential.
  • Careful consideration is required to ensure responsible and effective AI deployment.