Expanding on Total Body Score with Use of Geographic Information Systems (GIS)

As submitted by the proposer: The quantification of human decomposition is a difficult issue within forensic anthropology. However, many attempts have been made to both standardize and score decomposition with the intent of estimating a post-mortem interval (PMI) with known error ranges (for example, Megyesi et al., 2005). Yet, the Megyesi et al. method (2005), aka the total body score (TBS), has several limitations. First, many regions of the body are grouped together and scored as one unit, which diminishes the fidelity in recording the often asymmetric and highly variable decomposition processes. Second, the method does not address how to handle scavenged remains, which greatly accelerates decomposition processes. Third, the method was developed from photographs with a combination of known and estimated PMIs, thus introducing unnecessary statistical noise. The proposed research will enhance the quantification of variability in decomposition by breaking down the body into 16 discrete regions, with limb antimeres scored separately. The quantification of human decomposition is a difficult issue within forensic anthropology. However, many attempts have been made to both standardize and score decomposition with the intent of estimating a post-mortem interval (PMI) with known error ranges (for example, Megyesi et al., 2005). Yet, the Megyesi et al. method (2005), aka the total body score (TBS), has several limitations. First, many regions of the body are grouped together and scored as one unit, which diminishes the fidelity in recording the often asymmetric and highly variable decomposition processes. Second, the method does not address how to handle scavenged remains, which greatly accelerates decomposition processes. Third, the method was developed from photographs with a combination of known and estimated PMIs, thus introducing unnecessary statistical noise. The proposed research will enhance the quantification of variability in decomposition by breaking down the body into 16 discrete regions, with limb antimeres scored separately. Ten individuals will be placed in the same environment at the same time at the Anthropological Research Facility (ARF) at the University of Tennessee. Separate trials will be conducted in different seasons to capture the variability of decomposition by season. A modified trait list will be developed to record the presence or absence of discrete traits in the field that are later tied to a quasi-continuous weighted scoring system to minimize bias while collecting data. Two independent observers will score the same subjects each day. The associated scores will be input into a digitized homunculus into a geographic information system (GIS), ArcGIS (ESRI, 2011), each day for each individual in the study sample. At the end of each trial, the scores for each individual will be summed for each region of the body to create a heat map that will show individual regional variability in decomposition process. Further, the scores for each of the subjects in each trail will be summed upon collection and a heat map generated to show the overarching trends in decomposition. Hot spot analysis will then be performed on the combined heat maps to identify statistically significant hot (first to decompose) and cold (last to decompose) spots. Linear regression models will be created. The created models will then be validated on various holdout specimens. The proposed research will provide more precise PMI estimates and associated error ranges by capturing greater variability in the decomposition process. This project contains a research and/or development component, as defined in applicable law. ca/ncf