This project is to assess the public’s exposures to the roughly 10,000 chemicals in commerce. To achieve this goal novel approaches are required to assessing human exposure. Approaches are needed to better assess how exposures vary across individuals, how exposures in an individual will vary across time, and how an individual’s exposure to multiple sources can be assessed.
This project will explore the use of simulated individuals (agents) whose interactions with multiple sources can be tracked and used to characterize aggregate and cumulative exposures under different conditions.
Populations of agents can be used to study interactions with sources of chemical exposure that occur as the result of other agent’s behaviors. Such populations of agents can potentially describe variation across population in specific communities. This project will investigate the feasibility of generating such agents. This will be done by investigating the tools available to support simulations and prior attempts to predict consumer behavior using agents.
Based on this work, models will be produced where the agents’ heuristics are calibrated using both first principles and existing data (CHAD, NHANES, U.S. Census and other sources). The agents’ behaviors will be used to make testable predictions (prediction of activity patterns, product usage rates, biomontoring data, and etc.). These comparisons can be used to evaluate and, if needed, revise the models.
-PS. Please use mathlab/Simulink for modeling, simulations, and analyses
-Original Articles are scientific reports on the results of original research. Text is limited to 3500 words with a 250-word structured abstract, 5 tables/figures, and 40 references. Original articles should include a 50-word Implications and Contribution summary statement.
Research methodology should be Longitudinal