Artificial Intelligence, Big Data, and IoT in Public Health Surveillance: A Global Narrative Review
DOI:
https://doi.org/10.61978/medicor.v3i3.1084Keywords:
Digital Health Surveillance, Artificial Intelligence in Health, Big Data Analytics, Internet of Things Healthcare, Public Health Policy, Health Equity, Global Health GovernanceAbstract
The transformation of public health surveillance through digital technologies has significantly reshaped global health responses in the post-pandemic era. This narrative review synthesizes evidence from 2019 to 2025, highlighting the roles of artificial intelligence (AI), big data, and the Internet of Things (IoT) in improving outbreak forecasting, data integration, and real-time monitoring. While high-income countries demonstrate successful implementation due to robust infrastructures and governance, low- and middle-income nations face systemic barriers such as inadequate digital capacity and workforce limitations. Key challenges include fragmented systems, interoperability issues, and persistent digital divides. Policy coherence, investment in workforce training, and ethical data governance emerge as critical enablers of sustainable and equitable surveillance. The findings underscore the need for inclusive digital health strategies that extend beyond emergency responses to build resilient systems capable of addressing both emerging threats and long-term public health priorities.
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