A Conceptual Architecture for National Biosurveillance: Moving Beyond Situational Awareness to Enable Digital Detection of Emerging Threats

Abstract

Despite numerous calls for improvement, the US biosurveillance enterprise remains a patchwork of uncoordinated systems that fail to take advantage of the rapid progress in information processing, communication, and analytics made in the past decade. By synthesizing components from the extensive biosurveillance literature, we propose a conceptual framework for a national biosurveillance architecture and provide suggestions for implementation. The framework differs from the current federal biosurveillance development pathway in that it is not focused on systems useful for "situational awareness" but is instead focused on the long-term goal of having true warning capabilities. Therefore, a guiding design objective is the ability to digitally detect emerging threats that span jurisdictional boundaries, because attempting to solve the most challenging biosurveillance problem first provides the strongest foundation to meet simpler surveillance objectives. Core components of the vision are: (1) a whole-of-government approach to support currently disparate federal surveillance efforts that have a common data need, including those for food safety, vaccine and medical product safety, and infectious disease surveillance; (2) an information architecture that enables secure national access to electronic health records, yet does not require that data be sent to a centralized location for surveillance analysis; (3) an inference architecture that leverages advances in "big data" analytics and learning inference engines-a significant departure from the statistical process control paradigm that underpins nearly all current syndromic surveillance systems; and (4) an organizational architecture with a governance model aimed at establishing national biosurveillance as a critical part of the US national infrastructure. Although it will take many years to implement, and a national campaign of education and debate to acquire public buy-in for such a comprehensive system, the potential benefits warrant increased consideration by the US government.

Early detection of perceived risk among users of a UK travel health website compared with internet search activity and media coverage during the 2015–2016 Zika virus outbreak: an observational study

“… 10 Fourth, many syndromic surveillance systems set up in the 2000s have been discontinued due to high false positive rates, which have led some observers to ask for systems incorporating higher quality sensors to inform early responders more effectively. 24 Finally, some have advocated for surveillance systems based on voluntary panels of members of the public that should offer timeliness and a tentative compromise between the safety and limitations of traditional study designs and the promises and perils of crowd-based systems. 29 …”

Use of artificial intelligence in infectious diseases

“…Risk analysis will also depend on how we are able to integrate and verify the quality of input data, especially based on IoT. All this will be for a global benefit (Velsko and Bates, 2016).…”

Implementation System of a Biosurveillance System in the Republic of Korea and Its Legal Ramifications

“…And biosurveillance encompasses threats to human health that occur beyond administrative lines. 20 Biosurveillance systems screen for risk factors, facilitating rapid detection of a response to unspecified threats. The ultimate goal of biosurveillance is to enable a timely response by integrating data obtained from multiple agencies and disciplines.…”

“…A synthesized view enables stakeholders to visualize the integrated information using a shared platform, thus reducing the need for reporting and notification. 20,21 The risk is interpreted and tracked in near real-time. The final step of biosurveillance is an integrated response by stakeholders.…”