  Contact Tracing has been used to identify people who were in close proximity
to those infected with SARS-Cov2 coronavirus. A number of digital contract
tracing applications have been introduced to facilitate or complement physical
contact tracing. However, there are a number of privacy issues in the
implementation of contract tracing applications, which make people reluctant to
install or update their infection status on these applications. In this concept
paper, we present ideas from Graph Neural Networks and explainability, that
could improve trust in these applications, and encourage adoption by people.
