GHUCCTS Programs & Resources

The goal for the Environmental Determinants of Health (EDH) component is to leverage geospatial analysis and high-capacity computing to develop, implement, and support innovative projects that will identify and characterize social and physical environmental contributors to health risks, particularly in under-served populations.

The EDH component features a collaboration of the DC based GHUCCTS institutions with the Oak Ridge National Laboratories (ORNL) in Oak Ridge, Tennessee funded by the Department of Energy, specifically ORNL’s Advanced Computing in Health Sciences Section in the Computing and Computational Sciences Directorate. We also engage the DC Department of Health (DC DOH). The following resources have been, or are available for, GHUCCTS projects:

1. ORNL has leveraged three diverse high-performance computing architectures for analyzing and modeling health data which have been applied to publicly available datasets including The Cancer Genome Atlas (TCGA), clinicaltrials.gov, Semantic MEDLINE, openFDA, DocGraph, National Plan and Provider Enumeration System, and clinical partnerships. ORNL scientists, in consultation with the other participating GHUCCTS scientists, are developing an Environmental Deprivation Index to provide a cumulative measure of environmental adversity, and “Urban Pop” for the purpose of modelling indicators of social determinants of health (SDOH) in urban environments.
2. At Howard University, we have obtained data on live births and utilized tools from the DC, DOH to index social determinants of health including violent crime rates, access to transportation and proximity to health sites, and food deserts at the level of census tracts and proximal neighborhood groups.
3. The informatics teams at GU and MHRI are also utilizing DC Ward data to include SDOH in their health risk predictive modelling. 

Projects include: 1) Evaluating the relationships between geospatially determined indices of neighborhood stress designated for proximal neighborhood groups (e.g. violent death rate) as well as self-reported neighborhood stress indicators with subjective and objective measures of sleep health.  2) Utilization of appointment and hospitalization data from MHRI to model trajectories of health care for common chronic diseases before and during the COVID-19 pandemic. 3) Analysis of SDOH in maternal health and neonate health birth outcomes.

Co-Director: Anuj Kapadia, PhD

Anuj J. Kapadia is a Distinguished R&D Scientist and Section Head for Advanced Computing in Health Sciences at Oak Ridge National Laboratory (ORNL). He is also an Adjunct Professor of Radiology, Physics, and Medical Physics at Duke University, with a Ph.D. in Biomedical Engineering from Duke. His work focuses on artificial intelligence (AI), machine learning (ML), and simulation and modeling in health applications. With over 20 years of experience, Dr. Kapadia has expertise in neutron and X-ray scattering, Monte Carlo simulation development, and data analytics for security and medical applications. He has received significant recognition for his contributions to the field, including funding from prominent organizations like the DOE, DOD, NIH, and others. Dr. Kapadia is a fellow of AAPM and a senior member of IEEE and SPIE professional societies.

Co-Director: Thomas A. Mellman, MD
Professor of Psychiatry
Director of the Center for Clinical and Translational Research and Stress/Sleep Studies Program at Howard University College of Medicine.

Dr. Mellman is Professor of Psychiatry and Director of the Center for Clinical and Translational Research and Stress/Sleep Studies Program at Howard University College of Medicine. He is the principal investigator representing Howard for the Georgetown Howard Universities Center for Clinical and Translational Science supported by a Clinical Translational Science Award from NIH. 

He received training at the NIMH Division of Intramural Research Programs and has previously held faculty appointments and achieved the rank of Professor at the University of Miami and Dartmouth. Dr. Mellman has had continuous funding as PI on federal research grants since 1991 including a VA Merit award, and R01, R21, R34 and K24 awards from NIMH, NHLBI, NIMHD, and the DOD. His primary research interests have been the role of sleep in posttraumatic stress disorder (PTSD) and the role of sleep in the effects of stress on physical and emotional health. He has a consistent track record of mentoring junior investigators and interdisciplinary collaboration. He recently finished service as a member of the NIH study section for Mechanisms of Emotion Stress and Health, was previously a member of NIMH IRGs for Violence and Traumatic Stress and Interventions, and has served on several review committees for the NIH Roadmap and Department of Defense research programs. Dr. Mellman was a member of the original ISTSS committee for developing treatment guidelines for PTSD, APA committee for text revision of the DSM-IV, and the Institute of Medicine Committee for review of the evidence regarding the treatment of PTSD. He received the International Society for Traumatic Stress Studies distinguished mentorship award for 2016.

Alina Peluso, PhD

Alina Peluso is a research scientist in Biostatistics and Biomedical Informatics in the Advanced Computing for Health Sciences Section at ORNL. She holds a B.S. and M.S. in Statistics from the University of Milan-Bicocca and a Ph.D. in Statistics from Brunel University London. Her Ph.D. advanced regression models for discrete responses, including health policy evaluation and flexible Weibull-based models. She previously worked at Brunel University and Imperial College London, applying machine learning and statistical modeling to omics data for precision medicine. At ORNL, her research focuses on causal inference, environmental and disease epidemiology, and computational methods for statistical genomics. She contributes to key national projects such as cancer outcomes modeling (MOSSAIC), suicide risk modeling (REACH VET), and geospatial analyses of health impacts related to socioeconomic and environmental determinants, including the effects of COVID-19.

Additional team members:

• Kevin Sparks (Scientist, EDH datasets lead)
• Hilda Klasky (Scientist, Datasets and documentation)
• Joshua Grant (Scientist, Vizualization lead)
• Joe Tuccillo (Scientist, Synthetic populations)

Social and environmental conditions play a critical role in shaping health outcomes. These factors include the environments where individuals are born and live, their employment status, income, wealth, and educational attainment. The Social and Environmental Determinants of Health (SDOH) component integrates research on these social conditions and environmental exposures, as well as their interactions, to gain a deeper understanding of their combined effects on health. This component is essential as it addresses the root causes that influence health outcomes and disparities, providing critical insights for developing effective public health strategies and policy interventions.

The primary goal of the Social Determinants of Health (SDoH) and Environmental Determinants of Health (EDH) component at the Georgetown-Howard Universities Center for Clinical and Translational Science (GHUCCTS) is to advance our understanding of how social and environmental factors contribute to health outcomes and disparities across diverse populations. This component seeks to identify and address the broader determinants impacting public health by integrating comprehensive data on social conditions, environmental exposures, and their interactions with individual and community health outcomes. By leveraging GHUCCTS’s expertise, we aim to develop innovative methods for assessing and mitigating these determinants, thereby informing strategies to promote health equity and reduce disparities (type 1 translation). Additionally, our focus on policy analysis and community-based research will help assess how changes in social and environmental policies and resource allocation can lead to significant improvements in population health (type 2 translation). To achieve these goals, GHUCCTS will collaborate with key partners, including Oak Ridge National Laboratory (ORNL), to advance pioneering research and interventions in SDoH and EDH.

The SDoH and EDH component also emphasizes the education of researchers and their teams, enhancing their expertise in study design and methodology while fostering innovative approaches to addressing health disparities. Furthermore, it will establish robust data collection and engagement strategies within GHUCCTS to support the ongoing development of a skilled workforce dedicated to exploring and addressing the social and environmental factors influencing health outcomes.

• High-Performance Computing (HPC) Resources: Access to diverse HPC architectures from ORNL for analyzing and modeling health data, including large publicly available datasets such as The Cancer Genome Atlas (TCGA), clinicaltrials.gov, Semantic MEDLINE, and others.
  
  
• Geospatial Analysis Tools: Development and implementation of tools like the Environmental Deprivation Index and Urban Pop to model social determinants of health (SDOH) in urban environments.
  
  
• Collaborative Data Integration: Integration of live birth data, social determinants of health (violent crime rates, access to transportation, etc.), and health data (DC Ward data) for predictive modeling and analysis across partner institutions (Howard University, Georgetown University, and others).
  
  
• Health Risk Predictive Modeling: Utilization of geospatial and SDOH data to model and predict health risks, including the impact of social conditions on chronic disease trajectories, sleep health, and maternal and neonatal health outcomes.
  
  
• Project-Specific Analytics and Support: Support for research projects like evaluating relationships between neighborhood stress indicators and health outcomes (e.g., sleep health), and modeling healthcare trajectories during the COVID-19 pandemic using hospitalization and appointment data.
  
  
• Collaborative Research & Partnerships: Collaborative opportunities with partners like Oak Ridge National Laboratory (ORNL), the DC Department of Health, and other institutions to enhance research on social and environmental health determinants.
  
  
• Researcher Education and Workforce Development: Educational initiatives to improve the expertise of researchers in study design, data analysis, and methodology, with a focus on addressing health disparities and developing innovative approaches to SDOH and EDH.
  
  
• Data Collection and Engagement Strategies: Establishment of data collection frameworks and community engagement strategies to support ongoing research and workforce development focused on social and environmental determinants of health.