P036 – Forensic Intelligence Production through Dynamic Analysis of DNA Match Data in Co-offending Networks Combined with Police Information

10:25

Wednesday August 19^th

Station 08

Duration: 12 minutes

03. Human identification

Léo Lavergne

DNA match data obtained from crime scene investigation provides information about repeat offenders and co-offending. Comparing DNA results from a crime scene to an offender database makes it possible to obtain an identification, which is then passed on to police agencies for further investigation. On the other hand, a significant number of individuals remain known only through their DNA profile found at the crime scene; could something be done to help identify these unknown individuals. By using DNA match data, it has been demonstrated that unknown individuals are often part of criminal group ant the interactions are reflected in DNA profiles found on crime scenes, termed co-offending networks (Lavergne et al. 2022). We hypothesized that co-offending information from our DNA matches used in networks together with police data could produce forensic intelligence and help identify some of these unknown individuals. Therefore, starting from DNA match data co-offending networks, we proposed to add police information related to all criminal cases within a network as well as information related to known individuals potentially involved in these cases. If more information is needed, a second processing round can add individuals and cases. For instance, using crime types and dates of event, a more complete picture may emerge from which forensic intelligence can be produced. Using the date of event is essential in revealing the network’s dynamics. By analysing these dynamics and their evolution in time, it is possible to determine when criminal activity is most intense, particularly involving the unknown individuals and their partners. In the present study, we used 19 years of DNA match data from the “Laboratoire de sciences judiciaires et de médecine légale du Québec” (LSJML) which represents hundreds of networks. To develop our concept, we used four networks composed of various types of criminal offenses including at least one unknown individual. An analyst from the Sûreté du Québec, a highest-level police org in Quebec partnered with us, allowing DNA data to be combined to police information. We present examples of network dynamics that support our hypothesis. We show that using the LSJML complete DNA dataset along with the police information, our collaborating analyst was able to identify over a hundred previously unknown individuals.

Authors

Léo Lavergne (Université du Québec à Trois-Rivières, Canada)
Emmanuel milot (Université du Québec à Trois-Rivières, Canada)
Rémi Boivin (Université de Montréal, École de criminologie, Canada)
Simon Baechler (Université de Lauzanne, École de sciences criminelles, Switzerland)
Diane Séguin (Laboratoire de sciences judiciaires et de médecine légale, Canada)
Karine Fiola (Laboratoire de sciences judiciaires et de médecine légale, Canada)
Jean-Francois Lefebvre (Laboratoire de sciences judiciaires et de médecine légale, Canada)

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P036 – Forensic Intelligence Production through Dynamic Analysis of DNA Match Data in Co-offending Networks Combined with Police Information

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