Decomposition variability between the scene and autopsy examination and implications for post-mortem interval estimations

Evaluation of porcine decomposition and total body score (TBS) in a central European temperate forest

The total body score (TBS) is a visual scoring method to scale the succession of decomposition stages. It compares decomposition between cadavers, to connect it with external taphonomic factors and estimate the post-mortem interval. To study decomposition in various climatic environments, pigs are often used as human proxies. Currently, there is one TBS system by Keough et al. (J Forensic Sci. 2017;62:986) for surface-deposited domestic pigs, coming from South Africa. Our study aims to evaluate this method and analyze porcine decomposition in Central Europe to inform forensic research and casework. We conducted an experiment studying six 50 kg pig carcasses in a temperate Swiss forest. Three observers documented decomposition patterns and rated the decomposition stages from photographs based on the porcine TBS model by Keough et al. (J Forensic Sci. 2017;62:986). We documented discrepancies between the carcass decomposition of our specimens and those in the South African study, especially related to the high insect activity in our experiment. Furthermore, we noted factors complicating TBS scoring, including rainfall and scavengers. The agreement between TBS observers from photographs was in the highest agreement category apart from one "substantial agreement" category. Our study is the first in Europe to systematically test the Keough et al. (J Forensic Sci. 2017;62:986) method. The results evidence that regional adaptations are required to be applicable for other environments. We present a modified approach based on experimental observations in a Swiss temperate forest. The identification of regional decomposition patterns and drivers will inform future taphonomy research as well as forensic casework in comparable contexts in Central Europe.

A synthesis of carcass decomposition studies conducted at a tropical (Aw) taphonomy facility: 2013-2022

Decomposition studies have been conducted in several regions of the world, but relatively few have investigated taphonomy in tropical environments. Even fewer have explored carcass decomposition during multiple tropical seasons, leaving the relationships between season and decomposition in tropical environments poorly understood. Ten decomposition studies using 30 carcasses were conducted in Honolulu, Hawaii, USA to start addressing this knowledge gap. These studies show that some postmortem processes were observed regardless of season. Carcass temperature and chemistry were spatiotemporally variable. Fly larval masses were consistently observed within 3 days (∼75 ADD) postmortem and carcasses lost 60%-90% of mass by 10 days (∼250 ADD) postmortem (Total Body Score ∼26). Season had a significant effect on decomposition, yet the warmest and most humid seasons did not always result in the most rapid and extensive decomposition. Seasonal variation appears to be less pronounced than at other tropical decomposition sites.

Informing regional taphonomy research using retrospective forensic anthropology cases in the Western Cape, South Africa

The post-mortem interval (PMI) is important in death investigations as it can assist in reconstructing the context of the case and the identification of the unknown individual. However, in some instances the PMI is challenging to estimate due to the absence of regional taphonomy standards. To conduct accurate and locally relevant forensic taphonomy research, investigators require insight into the regional hotspot recovery areas. Thus, forensic cases examined by the Forensic Anthropology Cape Town (FACT) in the Western Cape (WC) province of South Africa between 2006 and 2018 (n = 172 cases; n = 174 individuals) were retrospectively reviewed. In our study, a considerable number of individuals did not have the PMI estimations (31 %; 54/174) and the ability to estimate a PMI was significantly associated with skeletal completeness, unburnt remains, absence of clothing and the absence of entomological evidence (p < 0.05 for each). Significantly fewer cases had the PMI estimated after FACT was formalised in 2014 (p < 0.0001). One third of cases with PMI estimations were made with large open-ended ranges, making them less informative. Factors significantly associated with these broad PMI ranges were fragmented remains, absence of clothing and absence of entomological evidence (p < 0.05 for each). Most decedents (51 %; 87/174) were discovered in police precincts from high crime areas, yet a considerable number (47 %; 81/174) were also found in low crime and sparsely populated areas regularly used for recreational activities. Common sites of body discovery were vegetated areas (23 %; 40/174), followed by the roadside (15 %; 29/174), aquatic environments (11 %; 20/174) and farms (11 %; 19/174). Decedents were discovered exposed (35 %; 62/174), covered with items such as bedding or shrubs (14 %; 25/174) or buried (10 %; 17/174). Our data highlight gaps in forensic taphonomy studies and clearly informs what regional research is needed. Overall, our study demonstrates how forensic case information can inform regional forensic taphonomy studies to locate common areas and contexts for the discovery of decomposed bodies and encourages similar studies in other areas of the world.

Solving the inverse problem of post-mortem interval estimation using Bayesian Belief Networks

Bayesian Belief Networks (BBNs) can be applied to solve inverse problems such as the post-mortem interval (PMI) by a simple and logical graphical representation of conditional dependencies between multiple taphonomic variables and the observable decomposition effect. This study is the first cross-comparison retrospective study of human decomposition across three different geographical regions. To assess the effect of the most influential taphonomic variables on the decomposition rate (as measured by the Total Decomposition Score (TDS)), decomposition data was examined from the Forensic Anthropology Research Facility at the University of Tennessee (n = 312), the Allegheny County Office of the Medical Examiner in Pittsburgh, US (n = 250), and the Crime Scene Investigation department at Southwest Forensics in the UK (n = 81). Two different BBNs for PMI estimations were created from the US and the UK training data. Sensitivity analysis was performed to identify the most influential parameters of TDS variance, with weaker variables (e.g., age, sex, clothing) being excluded during model refinement. The accuracy of the BBNs was then compared by additional validation cases: US (n = 28) and UK (n = 10). Both models conferred predictive power of the PMI and accounted for the unique combination of taphonomic variables affecting decomposition. Both models had a mean posterior probability of 86% (US) and 81% (UK) in favor of the experimental hypothesis (that the PMI was on, or less than, the prior last known alive date). Neither the US nor the UK datasets represented any cases below 'moderate' support for the value of PMI evidence. By applying coherent probabilistic reasoning to PMI estimations, one logical solution is provided to model the complexities of human decomposition that can quantify the combined effect of several uncertainties surrounding the PMI estimation. This approach communicates the PMI with an associated degree of confidence and provides predictive power on unknown PMI cases.