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Sampling strategy is one of the deciding factors in DNA typing success rates. Small amounts of bodily fluid traces and (skin) contact traces are currently not visualized in standard forensic practice. Trace recovery is usually based on the information available in a particular case and on the experience and 'forensic common sense' applied by the trace recovery expert. Interactions between an offender and a victim may have characteristic features, resulting in specific trace patterns. Understanding these interactions, and their resulting trace patterns, might improve crime related trace recovery as well as DNA typing success rates. In this study, we examined the interactions between offender and victim when a body has been relocated from one position/location to another. The contact between the hands of the offender and the body of the victim was visualized using a fluorescent dye in a lotion that was applied to the hands of the individual undertaking the relocation. The contact locations were scored and patterns were analyzed based on both victim and offender characteristics (height, weight, age, gender). The resulting patterns were compared to current trace recovery practices in the Netherlands. The results of this large-scale study facilitate evidence-based sampling supporting both investigative and evaluative forensic examinations., (Copyright © 2018 The Chartered Society of Forensic Sciences. Published by Elsevier B.V. All rights reserved.)

In forensic casework, evidence regarding the type of cell material contained in a stain can be crucial in determining what happened. For example, a DNA match in a sexual offense can become substantially more incriminating when there is evidence supporting that semen cells are present. Besides the question which cell types are present in a sample, also the question who donated what (association) is very relevant. This question is surprisingly difficult, even for stains with a single donor. The evidential value of a DNA profile needs to be combined with knowledge regarding the specificity and sensitivity of cell type tests. This, together with prior probabilities for the different donor-cell type combinations, determines the most likely combination. We present a Bayesian network that can assist in associating donors and cell types. A literature overview on the sensitivity and specificity of three cell type tests (PSA test for seminal fluid, RSID saliva and RSID semen) is helpful in assigning conditional probabilities. The Bayesian network is linked with a software package for interpreting mixed DNA profiles. This allows for a sensitivity analysis that shows to what extent the conclusion depends on the quantity of available research data. This can aid in making decisions regarding further research. It is shown that the common assumption that an individual (e.g. the victim) is one of the donors in a mixed DNA profile can have unwanted consequences for the association between donors and cell types., (Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.)

When a Y-chromosomal and a (partial) autosomal DNA profile are obtained from one crime sample, and both profiles match the suspect's profiles, we would like to know the combined evidential value. To calculate the likelihood ratio of observing the autosomal and Y-chromosomal DNA profiles combined, we need to know the conditional random match probability of the observed autosomal DNA profile, given the Y-chromosomal match. We examine this conditional probability in two ways: (1) with a database containing data of 2,085 men and (2) using a simulation model. We conclude that if the Y-chromosomal DNA profiles match, we can still regard the autosomal DNA profile as independent from the Y-chromosomal DNA profile if the matching person is not a descendant of the father of the donor of the (crime) sample. The evidential value can, in that case, be computed by multiplying the random match probabilities of the individual profiles.

In forensic casework it is common that multiple pieces of evidence are obtained in a single case. For the evaluation of such evidence, one cannot simply assume that they originated from the same source. If this can be disputed, one could decide to report the evidential value of the separate pieces by computing likelihood ratios (LRs) for them separately. However, by doing so, information regarding the conditional dependency structure is lost and the potentially difficult step of combining them is left to the trier of fact. Especially in situations where the pieces of evidence are of the same type, a combined evaluation could be substantially more informative. In such situations, it is not unrealistic that the separate evidential values are not optimally combined by the trier of fact. From a scientific point of view, the optimal way is that the forensic scientist combines the forensic evidence in a report using hypotheses at the 'activity level'. In practice, however, this is not always feasible for every case for reasons of efficiency. In this article, we explore what can be done in cases where the optimal solution is too costly. For a combined evaluation, the prior distribution for the number of distinct sources of the pieces of evidence becomes part of the LR. Generally, prior probabilities are beyond the scope of expertise of the forensic specialist and are left to the trier of fact to decide. We propose a lower bound LRapproach for such situations that is independent of the prior distribution. Using a set of examples, we present how this method can be applied in practice. [ABSTRACT FROM AUTHOR]

In this article, the performance of a score-based likelihood ratio (LR) system for comparisons of fingerprints with fingermarks is studied. The system is based on an automated fingerprint identification system (AFIS) comparison algorithm and focuses on fingerprint comparisons where the fingermarks contain 6-11 minutiae. The hypotheses under consideration are evaluated at the level of the person, not the finger. The LRs are presented with bootstrap intervals indicating the sampling uncertainty involved. Several aspects of the performance are measured: leave-one-out cross-validation is applied, and rates of misleading evidence are studied in two ways. A simulation study is performed to study the coverage of the bootstrap intervals. The results indicate that the evidential strength for same source comparisons that do not meet the Dutch twelve-point standard may be substantial. The methods used can be generalized to measure the performance of score-based LR systems in other fields of forensic science. [ABSTRACT FROM AUTHOR]

When a Y-chromosomal and a (partial) autosomal DNA profile are obtained from one crime sample, and both profiles match the suspect's profiles, we would like to know the combined evidential value. To calculate the likelihood ratio of observing the autosomal and Y-chromosomal DNA profiles combined, we need to know the conditional random match probability of the observed autosomal DNA profile, given the Y-chromosomal match. We examine this conditional probability in two ways: (1) with a database containing data of 2,085 men and (2) using a simulation model. We conclude that if the Y-chromosomal DNA profiles match, we can still regard the autosomal DNA profile as independent from the Y-chromosomal DNA profile if the matching person is not a descendant of the father of the donor of the (crime) sample. The evidential value can, in that case, be computed by multiplying the random match probabilities of the individual profiles. [ABSTRACT FROM AUTHOR]