Harnessing the potential of AI in public health: a narrative literature review of AI applications in zoonotic disease surveillance: a one health perspective

Abstract

Zoonotic diseases were recognized as a persistent threat to human health. Surveillance of zoonoses was considered a cornerstone of public health, aimed at mitigating and preventing outbreaks and spillovers. Evidence demonstrated the interconnectedness among human, animal, and environmental health, reinforcing the importance of addressing health through the One Health perspective. The importance of zoonotic disease surveillance under the One Health framework has been widely acknowledged over the last decades. However, the desired standards were not sufficiently met. The potential of artificial intelligence to facilitate the necessary changes in health systems was identified as a source of renewed optimism.

A narrative literature review was conducted to explore the topic comprehensively. A thorough search was performed across various online academic databases, such as Cochrane Library, PubMed, Science Direct, Sage Premier, and Savonia-Finna. Fifteen studies published in English between 2019 and 2025 were included. Grey literature was also incorporated using the same search parameters, broadening the scope of the review. Peer review and reflexive journaling were not performed, and no participants were involved, as the study was based solely on the analysis of existing literature.

A stronger zoonotic disease surveillance supported by ethical AI implementation offered a promising path to improve health systems, preventing and mitigating potential pandemics. Challenges such as coordination, governance, human and animal health transdisciplinary integration, and resource constraints were identified, emphasizing the need for a reinforced One Health approach. Further research was recommended to address these challenges and develop equitable and effective solutions.