Consideration of the probative value of single donor 15-plex STR profiles in UK populations and its presentation in UK courts.

The adoption of new 15 locus STR multiplex systems into UK forensic science would be facilitated by agreed guidelines for reporting the strength of DNA evidence using likelihood ratios. To facilitate such an agreement, we present an analysis of previously published UK allele frequencies for white Caucasian, Afro-Caribbean and Indo-Pakistani populations and investigate their effect on likelihood ratios for single donor profiles. We consider the implication of the five additional loci and suggest a procedure for reporting likelihood ratios for 15-plex STR profiles.

Quantitative assessment of evidential weight for a fingerprint comparison. Part II: a generalisation to take account of the general pattern.

The authors have proposed a quantitative method for assessing weight of evidence in the case where a fingermark from a crime scene is compared with a set of control prints from the ten fingers of a suspect. The approach is based on the notion of calculating a Likelihood Ratio (LR) that addresses a pair of propositions relating to the individual who left the crime mark. The current method considers only information extracted from minutiae, such as location, direction and type. It does not consider other information usually taken into account by fingerprint examiners, such as the general pattern of the ridge flow on the mark and the control prints. In this paper, we propose an improvement to our model that allows a fingerprint examiner to take advantage of pattern information when assessing the evidential weight to be assigned to a fingerprint comparison. We present an extension of the formal analysis proposed earlier and we illustrate our approach with an example.

A Bayesian approach for interpreting shoemark evidence in forensic casework: accounting for wear features.

Shoemark evidence remains a cornerstone of forensic crime investigation. Shoemarks can be used at a crime scene to reconstruct the course of events; they can be used as forensic intelligence tool to establish links between crime scenes; and when control material is available, used to help infer the participation of given individuals to the commission of a crime. Nevertheless, as for most other impression evidence, the current process used to evaluate and report the weight of shoemark evidence is under extreme scrutiny. Building on previous research, this paper proposes a model to evaluate shoemark evidence in a more transparent manner. The model is currently limited to sole pattern and wear characteristics. It does not account formally for cuts and other accidental damages. Furthermore, it requires the acquisition of relevant shoemark datasets and the development of automated comparison algorithms to deploy its full benefits. These are not currently available. Instead, we demonstrate, using casework examples, that a pragmatic consideration of the various variables of the model allows us to already evaluate shoemark evidence in a more transparent way and therefore begin to address the current scientific and legal concerns.

Quantitative assessment of evidential weight for a fingerprint comparison I. Generalisation to the comparison of a mark with set of ten prints from a suspect.

The authors have published elsewhere a quantitative method for assessing weight of evidence in the case where a finger mark from a crime scene is compared with a control print taken from a single finger of a suspect. The approach is based on the notion of calculating a likelihood ratio (LR) that addresses a pair of propositions relating to the single finger that was the origin of the crime mark. In practice, things are rather different because the crime mark will not just be compared with a single finger from a suspect but with a set of prints from all of his/her fingers; likewise, when the mark is compared with a database, this will consist of ten print records from random individuals. It is clear that "finger propositions" are not realistic in this situation and we show how our approach may be generalised to address a pair of propositions that relate to the person that made the crime mark. It often is the case that information is present at the crime scene that enables some inference to be drawn relating to which of the offender's ten fingers left a particular mark of interest. This kind of inference may profitably be drawn into the formal analysis. We illustrate our approach with an example.

Operational benefits and challenges of the use of fingerprint statistical models: a field study.

Research projects aimed at proposing fingerprint statistical models based on the likelihood ratio framework have shown that low quality finger impressions left on crime scenes may have significant evidential value. These impressions are currently either not recovered, considered to be of no value when first analyzed by fingerprint examiners, or lead to inconclusive results when compared to control prints. There are growing concerns within the fingerprint community that recovering and examining these low quality impressions will result in a significant increase of the workload of fingerprint units and ultimately of the number of backlogged cases. This study was designed to measure the number of impressions currently not recovered or not considered for examination, and to assess the usefulness of these impressions in terms of the number of additional detections that would result from their examination.