Improving the Sexual Assault Workflow - Efficient Sample Selection and Data Interpretation

The national backlog of untested rape kits continues to draw media attention. According to the Rape, Abuse and Incest National Network, an American is sexually assaulted every two minutes with over 235,000 sexual assaults occurring every year. Crime laboratories continue to face backlogs of DNA cases and often do not have sufficient resources to keep up with the growing demand for DNA casework. Law enforcement agencies may also be short-staffed and unable to keep up with sexual assault investigations. As a result, there is a growing backlog of untested rape kits nationwide and increasing political pressure to test every rape kit. If crime laboratories are going to process more rape kits with existing resources, more efficient methods need to be developed that still provide a thorough analysis of the rape kit evidence, coupled with robust data interpretation that will stand up to court scrutiny. While there have been many advancements in automated sample processing, a large production bottleneck exists in DNA data interpretation in many laboratories. Our ability to generate DNA profiles through automation is quickly outpacing crime laboratories’ ability to efficiently interpret them. This problem will be exacerbated in the future with the addition of more CODIS core STR loci. The use of modeling software for data interpretation could be greatly benefit crime lab productivity by streamlining the analysis of DNA data produced through the analysis of sexual assault evidence. The purpose of this project is to investigate ways to streamline the analysis of sexual assault evidence in two different areas. First, to identify key information or variables in the sexual assault victim’s medical history report that could make a significant difference in obtaining a DNA profile. This could improve lab efficiency by using case specific information to select samples most likely to yield DNA profiles, thus reducing the number of samples that need to be physically processed. Second, to validate a more efficient data interpretation method using probabilistic modeling software that can be run quickly and efficiently on standard desktop computers. This could reduce the amount of time what will be needed to evaluate DNA profiles from the newest generation of STR typing kits and also allows laboratories to report the results using likelihood ratios, putting the US on par with the rest of the international forensic community. ca/ncf