Electronic Thesis/Dissertation


Decision Support Tool For Mass Fatality Victim Identification Open Access

The current approach to mass fatality victim identification depends heavily upon technologically sophisticated forensic identification techniques such as dental records, fingerprints, and DNA. This is based upon forensic experts' high level of confidence that these methodologies provide a reliable match between deceased bodies and the records of missing persons. All of these methods, however, are costly, time-consuming, and resource-intensive; the availability of adequate technological resources for rapid body identification in the mass fatality context is therefore uncertain. Identification techniques that employ easily documented visible information (called conventional methods of identification), such as human physical attributes or personal effects (conventional evidence), are less labor-intensive and characterized as low technological requirements. Individual conventional evidence may not currently establish identity matching with an "adequate" level of confidence. Subjectivity common in collecting conventional evidence, together with the lack of standardized application of rules of comparison, have tagged these identification techniques with diminished forensic credibility. When appropriately managed and combined, however, conventional evidence may provide the basis for potentially effective and reliable human identification. The goal of this study is to develop a decision support tool for facilitating body identification in mass fatality incidents, particularly for developing countries with severe technology constraints. The tool employs selected human physical attributes as identification elements and utilizes forms and sketches specifically designed to collect ante-mortem (AM) and post-mortem (PM) conventional data in a format that reduces subjectivity and promotes rapid and accurate matching. A framework of similarity measures for diverse types of physical attributes is proposed. This allows computing an overall similarity score between pairs of AM and PM confronting records, where the highest score represents the highest probable AM match with a selected PM record. This system, prioritizing the AM records in an order reflecting their decreasing similarity, reduces the number of files that eventually need accessed for close examination by the authority establishing body identity. A proof-of concept simulation model is designed and conducted to test the system's concepts and explore the model's response under varied mass fatality incident scenarios.This research provides an effective tool for supporting victim identification in mass fatality incidents. By enhancing the objectivity and accuracy of the conventional identification process, the developed system increases the reliability of body identification using conventional evidence. This may reduce, under specific circumstances, the need to resort to technological methods of identification, or at least facilitate the efficiency of finding a technological match.

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