Address the difficulty in identifying the geographical origin of unidentified human remains in the US and to enhance forensic investigations by assessing variation within and between latinx individuals

This $180,000 Project Grant award from the National Institute of Justice (NIJ) under the CFDA 16.560 National Institute of Justice Research, Evaluation, and Development Project Grants program aims to address challenges in identifying the geographical origin of unidentified human remains, particularly for Latinx individuals, including undocumented border crossers. The multi-year project (2025-2029) will utilize a combination of genetic, craniometric, and isotopic analysis to develop a statistical model that can more accurately predict the region of origin for Latinx individuals encountered in forensic cases. The research will integrate data from Latin American reference samples to evaluate the efficacy of this multi-method approach compared to single or dual-method analyses. The expected work products include the statistical model and a robust dataset that can be used nationally and internationally for Latinx region of origin predictions. The research findings will be disseminated through academic publications and conferences.

Variation will be assessed through novel data combinations obtained from latin american countries to evaluate region of origin predictions of unidentified latinx individuals. This project will utilize a multi-method approach that combines genetic, craniometric, and isotopic analysis for geolocation estimation and human identification of forensic cases in the US, including cases involving latinx citizens and residents, daca recipients, documented migrants, and undocumented border crossers (UBCS). The multi-method approach aims to address the misclassification errors experienced by latinx individuals and UBCS that contribute to an identification bias that delays investigations and limits region of origin predictions. This research will integrate genetic, craniometric, and isotopic data from latin american reference samples with the goal of testing the utility of isotope analysis as a geospatial tool and evaluating the efficacy of a multi-method analysis for identifying geographic region of origin for latinx individuals and UBCS. The objectives of this research include collecting data from each line of evidence from latin american countries and utilizing machine learning methods to integrate the data and examine the variation and correlation structure of latinx populations. The goals and objectives will be accomplished through research questions that focus on 1) assessing stable isotope region of origin predictions compared to predictions determined through genetic and craniometric data, 2) the efficacy of machine learning methods, such as the application of a random forest model, to integrate the three lines of evidence for region of origin predictions, and 3) whether a multi-method analysis predicts an individuals region of origin more accurately than a dual or single-method analysis. The research design consists of a four-step methodological analysis including single, dual, and multi-method approaches of the robust dataset to be compiled for region of origin analysis. The expected work products include a statistical model that will provide a more accurate estimated region of origin of UBCS and a better understanding of the multi-method approach for use in latinx forensic cases. The dissemination plan for this project includes producing a robust dataset that can be utilized nationally and internationally for latinx region of origin predictions, and results produced will be disseminated at national and international conferences as well as open access academic journals. CA/NCF