AuthorsA. Elmokashfi, S. W. Funke, T. Klock, M. Kuchta, V. Naumova and J. J. Uv
EditorsA. Elmokashfi, O. Lysne and V. Naumova
TitleDigital tracing, validation, and reporting
AfilliationScientific Computing
Project(s)No Simula project
Publication TypeBook Chapter
Year of Publication2022
Book TitleSmittestopp − A Case Study on Digital Contact Tracing
PublisherSpringer International Publishing
Place PublishedCham
ISBN Number978-3-031-05466-2

Manual contact tracing has been a key component in controlling the outbreak of the COVID-19 pandemic. The identification and isolation of close contacts of confirmed cases have successfully interrupted transmission chains and reduced the disease spread. Even though manual contact tracing has been widely used, its practice has shown that it is slow and cannot be scaled up once the epidemic grows beyond the early phase. In this case, digital contact tracing can play a significant role in controlling the pandemic. In this chapter, based on our experience and lessons learned from the Smittestopp project, we discuss the main prerequisites for the efficient implementation and validation of digital contact tracing in a population. Specifically, we discuss how to translate a close contact defined for manual tracing to proximity events discovered by a phone, that is, how to define a meaningful risk score and validate the digital contact tracing. We discuss challenges related to each step and provide solutions to some of them, even though questions still remain.