DNA commission of the International society for forensic genetics: Assessing the value of forensic biological evidence - Guidelines highlighting the importance of propositions. Part II: Evaluation of biological traces considering activity level propositions.

The value of the evidence depends critically on propositions. In the second of two papers intended to provide advice to the community on difficult aspects of evaluation and the formulation of propositions, we focus primarily on activity level propositions. This helps the court address the question of "How did an individual's cell material get there?". In order to do this, we expand the framework outlined in the first companion paper. First, it is important not to conflate results and propositions. Statements given activity level propositions aim to help address issues of indirect vs direct transfer, and the time of the activity, but it is important to avoid use of the word 'transfer' in propositions. This is because propositions are assessed by the Court, but DNA transfer is a factor that scientists need to take into account for the interpretation of their results. Suitable activity level propositions are ideally set before knowledge of the results and address issues like: X stabbed Y vs. an unknown person stabbed Y but X met Y the day before. The scientist assigns the probability of the evidence, if each of the alternate propositions is true, to derive a likelihood ratio. To do this, the scientist asks: a) "what are the expectations if each of the propositions is true?" b) "What data are available to assist in the evaluation of the results given the propositions?" When presenting evidence, scientists work within the hierarchy of propositions framework. The value of evidence calculated for a DNA profile cannot be carried over to higher levels in the hierarchy - the calculations given sub-source, source and activity level propositions are all separate. A number of examples are provided to illustrate the principles espoused, and the criteria that such assessments should meet. Ideally in order to assign probabilities, the analyst should have/collect data that are relevant to the case in question. These data must be relevant to the case at hand and we encourage further research and collection of data to form knowledge bases. Bayesian Networks are extremely useful to help us think about a problem, because they force us to consider all relevant possibilities in a logical way. An example is provided.

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