Public Health Surveillance Meets Translational Informatics: A Desiderata

“Public health surveillance (PHS) is the ongoing and systematic collection, analysis, interpretation, and dissemination of data regarding a health-related event for use in public health action to reduce morbidity and mortality and to improve health.” As information technology gains acceptance as a core element of public health practice, many approaches to the design of PHS systems have been proposed, much has been spent implementing them, and expectations have been high. Unfortunately, the systems implemented so far have been criticized as having not met expectations, especially in the domain of early detection and bioterrorism readiness, or so-called syndromic surveillance (The term “syndromic surveillance” applies to monitoring health-related data that precede diagnosis to signal a sufficient probability of a case or an outbreak that warrants public health response.). There are no fully established frameworks to enable seamless interoperability, information sharing, and collaboration among PHS stakeholders and the technological and infrastructural requirements to fulfill the grand vision of initiatives such as the Public Health Information Network and National Health Information Network are poorly investigated and documented. In this article, we examine the current state of the conceptualization, design, analysis, and implementation of PHS systems from a translational informatics perspective. Although most examples in this article are informed by the needs of public health preparedness (syndromic and bioterrorism detection and response), we believe the framework we introduce is generalizable and applicable to the broader context of PHS systems. We also apply concepts from cognitive science and knowledge engineering to suggest directions for improvement and further research.