Modernizing public health surveillance for global health security leveraging AI

Abstract

An electronic public health surveillance (e-PHS) embracing One Health and participatory approaches will collect and analyze data at the human-animal-environment interface to enhance real-time information for the prevention and control of public health emergencies (PHE) such as infectious disease outbreaks. Yet full implementation is suboptimal worldwide. Leveraging the capabilities of emerging digital technologies legally and ethically, we described the scope, added benefits, and applicability of a novel cloud-based, artificial intelligence-enabled One Health Integrated Disease Surveillance and Response health information system (AI-OneHIS) data infrastructure for modernizing the existing traditional PHS models. This multifaceted innovation will ensure faster data capture, seamless interoperability of fragmented HIS, and precise decision support, while preserving their structures, functionalities, and capabilities for routine operations and data sovereignty. This should enable the prevention, timely detection, and effective response to PHE for improved health outcomes if implemented with fidelity on a strong governance-collaboration-informatics-analytics framework.

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