Activity-level evaluation of DNA transfer to stockings: comparisonof HaloGen with simplified contributor-based approaches
DNA findings on clothing are often evaluated at sub-source level to address whether a person contributed DNA to a sample. In many cases, however, the disputed issue is not whose DNA is present, but how the DNA was transferred. This paper applies the HaloGen framework to evaluate DNA findings on stockings under activity-level propositions. The data derive from controlled experiments, reported in a companion paper, comparing active contact, in which a person of interest pulled down a pair of stockings, with social contact, in which the person of interest and wearer used the same bathroom. Contributor-specific DNA quantities were estimated for the person of interest and for observed unknown contributors across two sampled stains. Compatibility diagnostics indicated that the stockings dataset was broadly compatible with the observed Pop20 reference range. Pop20 was therefore used as regularising prior information in the Lab-Bayes model, rather than as a stand-alone Group model. Because the stockings dataset was generated in a single laboratory, transfer data from 20 laboratories were used as regularising prior information for a laboratory-specific Lab-Bayes model. The local stockings data then updated the direct- and secondary-transfer parameter distributions. Compatibility diagnostics indicated that the stockings dataset was broadly compatible with the observed Pop20 reference range. Pop20 was therefore used as regularising prior information in the Lab-Bayes model, rather than as a stand-alone Group model. In addition, prior-sensitivity and leave-one-case-out analyses indicated that the case-level likelihood ratios were not materially affected by the choice of prior specification or by data reuse. HaloGen likelihood ratios were assessed using Tippett plots and compared with simplified contributor-based comparator approaches. These approaches represent simplified forms of activity-level reasoning in which the DNA result is reduced to binary or categorical states. They comprise a binary source-support approach, a discrete Mx component-size approach, and a background approach based on the ReAct I Experiment 3 formulation. These approaches were used to examine the effect of reducing continuous contributor-specific DNA quantities to binary or categorical states, and to assess how the likelihood ratio is affected when observed unknown contributors are represented through a background/direct-unknown term rather than evaluated explicitly as possible alternative direct actors. HaloGen showed clear discrimination between active-contact and social-contact ground-truth cases. The simplified comparator methods illustrated the information loss caused by thresholding or categorising continuous DNA quantities. The ReAct background approach tended to shift direct-transfer likelihood ratios upward relative to the HaloGen calculation, showing that the treatment of observed unknown contributors can materially affect activity-level inference. The results support the importance of preserving contributor-level symmetry: an observed unknown contributor should not automatically be demoted to background when that contributor may represent an alternative direct actor under the defence proposition.