Predicting post-mortem interval of porcine remains in Choba, southern Nigeria using accumulated degree days and total body score

Abstract

Background: Accurate post-mortem interval (PMI) estimation is fundamental to death investigations, yet forensic models from temperate regions often fail in tropical climates. This study evaluated the reliability of accumulated degree days (ADD) and total body score (TBS) for PMI estimation in the distinct seasonal environment of Choba, southern Nigeria. Methods: We monitored the decomposition of six porcine carcasses as human analogues across dry and rainy seasons. A regionally adapted Total Body Score system was applied daily. Ambient temperature data were collected to calculate ADD. Seasonal predictive models for PMI were generated using multiple regression analysis. Results: During the dry season, both ADD and TBS strongly predicted PMI, forming a robust model (R² = 0.863). In the rainy season, despite a high overall correlation, neither variable was a significant independent predictor, although the model explained substantial variance (R² = 0.916). Conclusions: While ADD and TBS are effective for PMI estimation in dry tropical conditions, their predictive utility is significantly confounded by wet season factors like rainfall and humidity. This underscores an urgent need for season-specific forensic models in tropical West Africa to improve investigative accuracy.