Microbial and seminal traces of sexual intercourse and forensic implications

Background The increasing numbers of sexual violence and unresolved rape cases require alternative approaches with higher evidential value to complement existing forensic tools. Predicting recent intercourse is crucial in forensic casework on sexual assaults. In this work, we assessed whether sexual intercourse can be predicted based on the vaginal microbiome and compared it to the gold standard method of semen detection. Results Using a prediction model based on microbiome of 3043 women, intercourse was predicted with 71% accuracy in a balanced cross-validation machine learning setting. This prediction model was validated in a longitudinal intervention study and tested on forensic sexual assault cases. The developed predictor could accurately establish intercourse in 82% of the studied cases. Yet, underwear was found to hold an even greater evidential value and replace the more invasive vaginal sampling for semen detection in some cases with an accuracy of 95%. This was substantiated through a retrospective analysis of 207 forensic sexual assault cases. Conclusions Taken together, this study revealed that the vaginal microbiome is better at predicting recent sexual intercourse, while the victim’s underwear has a clear value as additional biological trace evidence for semen detection. These findings are particularly useful in cases with delayed reporting and are obtained with less invasive sampling.