  Graphical models and likelihood ratios can be used by forensic scientists to
compare support given by evidence to propositions put forward by competing
parties during court proceedings. Such models can also be used to evaluate
support for activity-level propositions, i.e. propositions that refer to the
nature of activities associated with evidence and how this evidence came to be
at a crime scene. Graphical methods can be used to show explicitly different
scenarios that might explain the evidence in a case and to distinguish between
evidence requiring evaluation by a jury and quantifiable evidence from the
crime scene. Such visual representations can be helpful for forensic
practitioners, the police and lawyers who may need to assess the value that
different pieces of evidence make to their arguments in a case. In this paper
we demonstrate for the first time how chain event graphs can be applied to a
criminal case involving drug trafficking. We show how different types of
evidence (i.e. expert judgement and data collected from a crime scene) can be
combined using a chain event graph and show how the hierarchical model deriving
from the graph can be used to evaluate the degree of support for different
activity-level propositions in the case. We also develop a modification of the
standard chain event graph to simplify their use in forensic applications.
