In cases of sexual assault, the interpretation of biological traces on clothing, and particularly undergarments, may be complex. This is especially so when the complainant and defendant interact socially, for instance as (ex-)partners or by co-habitation. Here we present the results from a study where latent male DNA on female worn undergarments is recovered in four groups with different levels of male-female social interaction. The results conform to prior expectation, in that less interaction tend to result in less male DNA on undergarments. We explore the use of these experimental data for evaluative reporting given activity level propositions in a mock case scenario. We show how the selection of different populations to represent the social interaction between complainant and defendant may affect the strength of the evidence. We further show how datasets of limited size can be used for robust activity level evaluative reporting.
MULTIFILE
In this study, we assessed to what extent data on the subject of TPPR (transfer, persistence, prevalence, recovery) that are obtained through an older STR typing kit can be used in an activity-level evaluation for a case profiled with a more modern STR kit. Newer kits generally hold more loci and may show higher sensitivity especially when reduced reaction volumes are used, and this could increase the evidential value at the source level. On the other hand, the increased genotyping information may invoke a higher number of contributors in the weight of evidence calculations, which could affect the evidential values as well. An activity scenario well explored in earlier studies [1,2] was redone using volunteers with known DNA profiles. DNA extracts were analyzed with three different approaches, namely using the optimal DNA input for (1) an older and (2) a newer STR typing system, and (3) using a standard, volume-based input combined with replicate PCR analysis with only the newer STR kit. The genotyping results were analyzed for various aspects such as percentage detected alleles and relative peak height contribution for background and the contributors known to be involved in the activity. Next, source-level LRs were calculated and the same trends were observed with regard to inclusionary and exclusionary LRs for persons who had or had not been in direct contact with the sampled areas. We subsequently assessed the impact on the outcome of the activity-level evaluation in an exemplary case by applying the assigned probabilities to a Bayesian network. We infer that data from different STR kits can be combined in the activity-level evaluations.
