The Decision Science Core is concerned with methods and approaches that can enable the four Texas A&M Superfund Research Center projects to understand and increase the effectiveness of decision-making by helping to determine the overall impacts of chemical exposures following an environmental disaster in terms of both health and economic standpoints. Specifically, using computer-based models, this core helps investigators convert environmental and biological measurements into predictions of chemically related health effects and economic costs that are used as benchmarks for risk management decisions. Directed by Weihsueh Chiu, at Texas A&M University, in collaboration with Gregory Characklis, at the University of North Carolina at Chapel Hill, the core also will serve as a bridge to the Community Engagement and Research Translation cores by assisting in the interpretation and translation of the projects’ conclusions into information that can be used by various stakeholders, including first responders, impacted communities, and governmental bodies involved in site management and cleanup.
- Apply and advance methods for toxicokinetic modeling-based dosimetry calculations for individual chemicals, defined mixtures, and environmental mixtures that will be used in Projects 3 and 4. The oral doses produced in early stages will be used by various stakeholders to prioritize chemicals and mixtures in the planning of, response to, and long-term recovery from environmental emergency-related contamination events.
- Apply and advance methods to create human health risk models that will allow decision-makers to predict hazards and risks for individual chemicals, defined mixtures, and environmental mixtures.
- Apply and advance economic modeling methods that rigorously estimate the benefits and costs associated with contamination events for individual chemicals, defined mixtures, and environmental mixtures. Using state-of-the-art economic modeling approaches, the Core will support the projects’ efforts in community engagement and research translation by converting hazard and risk estimates into economic terms (e.g., quality-adjusted life-years, dollars).