  Digital contact tracing has been deployed as a public health intervention to
help suppress the spread of COVID-19 in many jurisdictions. However, most
governments have struggled with low uptake and participation rates, limiting
the effectiveness of the tool. This paper characterises a number of systems
developed around the world, comparing the uptake rates for systems with
different technology, data architectures, and mandates. The paper then
introduces the MAST framework (motivation, access, skills, and trust), adapted
from the digital inclusion literature, to explore the drivers and barriers that
influence people's decisions to participate or not in digital contact tracing
systems. Finally, the paper discusses some suggestions for policymakers on how
to influence those drivers and barriers in order to improve uptake rates.
Examples from existing digital contact tracing systems are presented
throughout, although more empirical experimentation is required to support more
concrete conclusions on what works.
