A Concept of Operations to Embody the Utilization of a Distributed Test, Track and Track System for Epidemic Containment Management

Abstract

The severe acute respiratory syndrome coronavirus 2 pandemic revealed that many countries had insufficient strategies to conduct test, track, and trace of the viral transmission once infected people entered a country’s borders. Computer science could be used to understand the seats of infection, and hotspots that may fuel potential outbreaks. As well as the added benefit of steering on-the-ground epidemiological surveillance activities to contain further outbreaks. However, there is more to a computerized solution than an architectural design of an end-to-end distributed test, track, and trace system and its use of machine learning technologies. A successful implementation encompasses a number of key areas that include people, processes, and technology. Comparisons are drawn with cyber security operations center use-cases in support of a strategy and concept of operations to enable: (a) front-end test teams at the border chokepoints to collect test samples; (b) cloud processing of test subject records and laboratory test results; (c) emergency operations center containment monitoring; (d) data analysis of test subject groupings to identify hotspot areas; (e) use of epidemiological trends to direct further testing; and (f) conduct epidemiological monitoring to detect new chains of transmission.