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Cross-Border Threat Screening and Supply Chain Defense

A Department of Homeland Security Center of Excellence

Bayesian Risk Modeling

Issue:

Mexico became the top U.S. trade partner in 2020 according to U.S. Census. While Canada remained as No. 2 U.S. trade partner for the fifth consecutive year, followed by China in the third position.  These shifts and the framework outlined in the ‘United States-Mexico-Canada Agreement (USMCA), make the region one most important trade and supply chain regions in the world. The COVID-19 epidemic and Russia’s attempted invasion of Ukraine highlight the many different threats facing North American and global supply chains, yet those are just a few of the many social, economic, and environmental, climatic, and logistical risks that could be assessed.

Objectives:

  1. To expand U.S.-Mexico Taskforce to include Canadian representatives from government, academia, industry, and community-based organizations, with a focus on global competencies.
  2. To expand Data-Lake System’s infrastructure and Data-Management Workflow to expedite and multiply the production of risk-based analytics.
  3. To foster collaborations with other supply chain projects with a focus on strategic collection of supply chain evidence.
  4. To expand the availability of evidence to inform Risk Minimum viable Models (RMVMs), for the Calibration, Testing and Simulation of specific supply chain case studies.
Technical Illustration from Bayesian Risk modeling project

Value Proposition:

The integration of the Risk Taskforce for North America (MEX-USA-CAN) will facilitate the establishment of multiple international collaborations for the identification and characterization of variables/processes defined specific supply chains RMVMs and case studies. The expansion of Data-Lake System’s infrastructure and Data-Management Workflow enables more rapid development of risk analytics based on input from multiple remote collaborators (Dataiku), and open of collaborations other evidence-driven projects. Finally, this work will support RMVMs ability to identify and characterize evidence, produce of risk-based analytics to Calibrate, Test and Simulate, social, economic and environmental States of Risk, and produce nine case studies that reflect varying availability of data, models and expertise on which to base risk assessments for chains that represent a range of complexities.

Project Lead Texas A&M University – College of Engineering
Research TeamPI: Zenon Medina-Cetina, Ph.D., Texas A&M University (TAMU), College of Engineering, College of Geosciences
Co-PI: Dennis Gorman, Ph.D., TAMU, School of Public Health
Co-PI: Julie Loisel, Ph.D., TAMU, College of Engineering College of Geosciences
Budget$1,196,969
DurationAug. 2022 – Aug. 2024