Propositions

Sub-source likelihood ratios were calculated for both contributors using EuroForMix [20], although this information was not used in any further analysis. To proceed with activity level analysis, it is assumed that the sub-source LR is sufficient for a court to agree the identity of a POI [2].

The prosecution and defence activity level propositions are as follows:

*Hp*: A and B packed the drugs together and B did not previously handle the tape;

*Hd*: A packed the drugs alone; B had previously handled the tape

From the case information, a Bayesian network incorporating the relevant nodes was prepared (Figure 9). See Supplementary Materials S1 for details. Since both *Hp* and *Hd* agree that contributor A packed the drugs, his/her presence or absence of DNA has no effect upon the likelihood ratio. Only contributor B has an effect.

**Figure 9.** Bayesian network for the evaluation of evidence in the case where DNA evidence was collected from cardboard drug wrap.

### Statistical Analysis

The data are provided in Supplementary Materials S2. In the experiment, contributor B previously handled the tape as described in Section 3.5.1, and contributor A packed the drugs. The mean *RFU* of the observed DNA profile was split per contributor (*RFUA* and *RFUB*), based upon their respective mixture proportions ( *Mx*): i.e., *RFUA* = *RFUtot* × *MxA* and *RFUB* = *RFUtot* × *MxB*, where *Mx* was calculated using EuroForMix [20]. Log-normal distributions were fitted to each set of data using the *fitdistrplus* R package (Figure 10). Distributions for the BN node "B DNA transferred when handling tape" (Figure 9) were modelled from *RFUC*2*tape*; distributions for BN nodes" (solo) A DNA transferred during packing" and "(joint) B DNA transferred during the packing" were both modelled from *RFUC*<sup>1</sup>*pac<sup>k</sup>* (Table 5).

**Figure 10.** Lognormal distributions of *RFUC*<sup>1</sup>*pac<sup>k</sup>* and *RFUC*<sup>2</sup>*tape*.

**Table 5.** Relationship of probabilities of DNA transfer from individuals A and B, showing the datasets that were used to calculate probability distributions, along with the BN nodes instantiated. Nomenclature is described in Section 2.5.1.


Likelihood ratios were calculated as follows (see Table 5 for context):


The formulae are derived in Supplementary Material S1. Note that likelihood ratios of (a) and (d) are the same, as are (b) and (c). This is because both *Hp* and *Hd* condition upon contributor A, hence his/her presence is cancelled out. To carry out sensitivity analysis, 1000× bootstraps (with replacement) were taken of the *RFUA* and *RFUB* data (Supplementary Material S1). For each bootstrap, a new set of log-normal parameters (mean log and SD log) were calculated using the *fitdistrplus* R package.

### Results of Analysis

Log-normal distributions were used to calculate the tape handling and drug packing TPR probabilities, conditioned upon values of *RFUB* > *x* from simulated profiles and subsequently used in the BN (Figure 8) to calculate the results (Table 6).


**Table 6.** Activity level likelihood ratios, with sensitivity analysis, showing 1–99 percentiles. The median (50 percentile) values are those that are reported. Results for the discrete model are shown in the top row; continuous model conditioned upon *RFUB* > *x* shown in remaining rows.

Likelihood ratios, along with sensitivity analyses are calculated against a range of *RFUB* > *x* values (Table 6). If a profile is obtained where only contributor A is present and there is no DNA present that can be attributed to contributor B, then the LR = 0.6, i.e., supports the proposition that suspect B did not package the drugs. If DNA is present that can be attributed to B, then the LR > 1, favouring the proposition that suspect B did package the drugs. The presence/absence of individual B as a contributor to the evidence can be described either as discrete: Pr(*RFUB* > 0) vs. absence, or as a continuous distribution where Pr(*RFUB* > *x*), where x is a threshold value. With a discrete model, LR=1.4 (first row of Table 6). Taking the value of *RFUB* > *x*, with the continuous model in subsequent rows of Table 6, a higher LR is achieved, reaching a maximum median LR=6.9 if RFUB > 1000 (the limit of observations in Supplementary Materials S2), although the evidence can only be described as "weak" following the ENFSI verbal scale [22]. The sensitivity analysis shows the observed range between 1–99 percentiles from 1000× bootstraps of the data. The variation increases greatly as *RFUB* increases—a reflection of the small size of the datasets. In conclusion, the discrete model understates the value of the evidence, compared with the continuous model.

### **4. Discussion**

#### *4.1. Zip-Lock Drugs Bag Experiment*

The DNA from the POI was detected more frequently on a zip-lock drugs bag if the bag was directly handled. However, the best quality profile observed in the study was collected from a zip-lock drugs bag stored in a personal bag (purse). From the literature, indirect transfer to a sleek surface such as the zip-lock drugs bag is expected to be low [8]. Most of the personal bags used in the experiments had previously been frequently used by the participants, although there are few observations in each class of bags, there is an indication that larger quantities of DNA can be detected on a zip-lock drugs bag after storage in purses. More DNA could be accumulated from the user on the inside of a purse as several personal items (e.g., phone, hairbrush, wallet) containing owner DNA are frequently stored there. In addition, the surface of the inside of the bag will influence accumulation and further transfer [8,23]. In the case example, it is shown that personal bags that are used to store everyday items, such as clothing or personal effects that are frequently handled, accumulate amounts of DNA that may be indirectly transferred to other objects. This resulted in low likelihood ratios (moderate evidence to support *Hp*) when DNA from only the POI was recovered. There was little difference between the discrete model and the continuous model, the latter takes the allele peak height into account. With mixtures, both discrete and continuous models favour *Hd* (LR ≈ 0.1; Table 4). In the experiment, only low amounts of background (DNA from unknown contributors) were detected. Combined with the relatively low difference between indirect and direct transfer

probabilities (Figure 8), especially when *RFU* > 1000, this has an impact of reducing the LR if the sample is in admixture with an unknown contributor, so that it always favours the defence proposition ( *Hd*).

#### *4.2. Cardboard Drug Wrap Experiment*

In this study, the persistence of DNA from previous handlers of a roll of tape was investigated. As the top surface of the tape is hard and non-porous, the expectation is that low amounts of DNA would be transferred and detected after direct contact, in addition to a rapid removal of DNA from the previous user [8,12,13]. The findings of this study generally correlate with these expectations: a large proportion of samples produced no results or only a few alleles. The packer (last handler) was the only contributor or the one contributing a larger amount of DNA in most of the samples that gave results. Some exceptions were observed with two profiles showing results that only corresponded to the tape handler (person B). The sides of the tape have a rougher surface where more DNA is expected to be transferred upon initial contact [9,23]. In addition to DNA from the previous user persisting on the surface of the tape, it is possible that some of the DNA deposited on the side of tape could be transferred to the new user's hands and to the cardboard during the wrapping of the drugs. As no other items were touched in between handling the tape and performing the wrapping, there was no opportunity for the loss of person B's DNA to other surfaces. We did not monitor the wrapping procedure and recognise that the manner of contact during the procedure could influence the result. However, information regarding this will rarely be known in casework.

In the Bayesian network case example, we considered that an individual B claims that he/she handled tape which was later used to prepare drug wraps. Individual A has admitted the offence, hence, his/her presence of DNA on the drug wrap has no bearing on the value of the evidence. If contributor B's DNA is recovered, without taking account of *RFU* in the discrete model, the evidence is close to neutral LR = 1.4, whereas if *RFU* is taken into account, the value of the evidence increases with RFU, although it does not exceed LR = 7 where *RFU* > 1000 (the upper limit of experimental observations), i.e., the evidence would be described as weak using the ENFSI scale [22]. However, if B's DNA is absent, then this favours the defence proposition LR = 0.6.

The experimental set up is similar to that used in [13] where the question was if the POI previously cut an aluminium foil or used this foil in lock picking. The activity LR in the lock-picking study, calculated with a discrete model (7.4) was greater than that observed in the current study (1.4). However, the LR was in the same range as the maximum (median) level of the continuous model employed (LR = 6.9). Some of the differences could be explained by the difference in transfer to and persistence on aluminium foil vs. tape.

#### *4.3. Shedder Status and Transfer Probabilities*

A person's shedder status has previously been shown to influence the probability of transfer, persistence, and detection of DNA [14,24]. Fonneløp et al. [14] demonstrated that DNA was more frequently detected in samples collected from the T-shirts of a victim if the attacker was a high shedder and that the probability of detection increased further if the victim was a low shedder. While Otten et al. [24] observed a correspondence between shedder stratus and DNA transfer to gloves. The correspondence between shedder status and the amount of DNA transferred is further demonstrated by our findings when it comes to direct transfer to zip-lock drugs bags (Figure 11), direct transfer during wrapping with a tape and transfer and persistence after touching a role of tape. On the other hand, when indirect transfer from the inside of a personal bag was considered, no clear association with shedder status was observed, and the best quality profile was detected after storage in a low shedder's personal bag. We hypothesised the amount of previous use and the surface of the inside of the bag could be of higher importance for this type of transfer. The low number of samples collected in each category is also a limitation and a clearer correspondence may be seen with a larger collection of data. Shedder status was not incorporated into the Bayesian

networks because dividing the results into three categories would lead to too few data in each group to analyse. Secondly, it would also be important to properly characterise the effect of shedder status on indirect transfer before applying this variable to the model.

**Figure 11.** Effect of high/medium/low shedder status on direct transfer (E1) data.

The LRs calculated in this study are comparable to other studies where DNA transferred by hands is considered [6,13,25]. It is likely that including more information— especially shedder status, would, to some degree, change the LR calculations [14].

#### *4.4. Detection of Unknown DNA*

This experiment was performed during the COVID-19 pandemic where a general recommendation to keep a social distance of at least two meters and to wash hands frequently or use antibacterial liquid was given. It is likely that these measures could have had an impact on the detection of unknown DNA in the samples, which was low compared to previous studies [9,16,26].

### **5. Conclusions**

We have created datasets on direct and indirect transfer to zip-lock bags and transfer and persistence to tape and further shown how the data can be used to inform Bayesian Networks. As the indirect and persistence scenarios tested are realistic under the circumstances utilised in this study, only moderate to low support for *Hp* was obtained. We have shown that applying a continuous model based on the profile quality can alter LRs compared to a discrete model and is preferable. There are challenges with limited datasets, and we were not able to implement shedder status into our models. More data on the influence of shedder status are required when indirect transfer is considered.

**Supplementary Materials:** The following are available online at https://www.mdpi.com/article/ 10.3390/genes13010018/s1, Supplementary Material S1: Derivation of formulae from experiment 2: Cardboard drug wraps, Supplementary Material S2: Supplementary table 2.1 Results from the direct and indirect transfer to zip-lock bags experiment; Supplementary table 2.2 Results from the persistence and detection of DNA from a previous user of a tape roll experiment; Supplementary table 2.3 The results of the shedder status experiment.

**Author Contributions:** Conceptualization, A.E.F. methodology, A.E.F. and P.G..; software, P.G.; formal analysis, A.E.F., S.F. and P.G.; investigation, S.F and G.S.; data curation, A.E.F. and S.F.; writing— original draft preparation, A.E.F., S.F. and P.G.; writing—review and editing, G.S.; supervision, A.E.F. and G.S.; project administration, A.E.F. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Institutional Review Board Statement:** This project was approved by the data protection officer at Oslo University Hospital (Approval Code: 20/22532, Approval Date: 21 October 2020).

**Informed Consent Statement:** Informed consent was obtained from all participants involved in the study.

**Data Availability Statement:** The data supporting the findings reported in this manuscript can be found in the supplementary material S2, Tables S1–S3.

**Acknowledgments:** We would like to thank Arne Roseth for his help with the direct PCR analysis and all the participants that contributed to the study.

**Conflicts of Interest:** The authors declare no conflict of interest.
