Technological innovations enable rapid DNA analysis implementation possibilities. Concordantly, rapid DNA devices are being used in practice. However, the effects of implementing rapid DNA technologies in the crime scene investigation procedure have only been evaluated to a limited extent. In this study a field experiment was set up comparing 47 real crime scene cases following a rapid DNA analysis procedure outside of the laboratory (decentral), with 50 cases following the regular DNA analysis procedure at the forensic laboratory. The impact on duration of the investigative process, and on the quality of the analyzed trace results (97 blood and 38 saliva traces) was measured. The results of the study show that the duration of the investigation process has been significantly reduced in cases where the decentral rapid DNA procedure was deployed, compared to cases where the regular procedure was used. Most of the delay in the regular process lies in the procedural steps during the police investigation, not in the DNA analysis, which highlights the importance of an effective work process and having sufficient capacity available. This study also shows that rapid DNA techniques are less sensitive than regular DNA analysis equipment. The device used in this study was only to a limited extent suitable for the analysis of saliva traces secured at the crime scene and can mainly be used for the analysis of visible blood traces with an expected high DNA quantity of a single donor.
Fingermarks are highly relevant in criminal investigations for individualization purposes. In some cases, the question in court changes from ‘Who is the source of the fingermarks?’ to ‘How did the fingermark end up on the surface?’. In this paper, we explore evaluation of fingermarks given activity level propositions by using Bayesian networks. The variables that provide information on activity level questions for fingermarks are identified and their current state of knowledge with regards to fingermarks is discussed. We identified the variables transfer, persistency, recovery, background fingermarks, location of the fingermarks, direction of the fingermarks, the area of friction ridge skin that left the mark and pressure distortions as variables that may provide information on how a fingermark ended up on a surface. Using three case examples, we show how Bayesian networks can be used for the evaluation of fingermarks given activity level propositions.