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A Conceptual Framework for Representing Events Under Public Health Surveillance
Anya Okhmatovskaia, Yannan Shen, Iris Ganser, Nigel Collier, Nicholas B. King, Zaiqiao Meng, David L. Buckeridge
387 - 391
10.3233/SHTI220480
Research Article
Studies in Health Technology and Informatics
Volume 294: Challenges of Trustable AI and Added-Value on Health
Abstract

Information integration across multiple event-based surveillance (EBS) systems has been shown to improve global disease surveillance in experimental settings. In practice, however, integration does not occur due to the lack of a common conceptual framework for encoding data within EBS systems. We aim to address this gap by proposing a candidate conceptual framework for representing events and related concepts in the domain of public health surveillance.

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