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Environmental and Health Risk Modeling Course at University of Michigan

Event date: 
2 January 2014 to 24 April 2014
Event time: 
15:00 - 18:00
University of Michigan, School of Public Health
1415 Washington Heights, Ann Arbor, MI 48109-2029, United States
Event details: 

- Which substances should the US EPA prioritize for further study, in order to protect human health and ecosystem quality?
- What fraction of a chemical emitted at a stack is inhaled or ingested via the food chain by the population? What about the use of cosmetics? How do nanoparticles distribute in human bodies?
- Why could low levels of antibiotics in the environment promote antibiotic resistant bacteria?

To learn how to use and develop environmental models to address these questions, we offer this winter a new course in Environmental and Health Risk Modeling (EHS 796-002, Special Topics in Environmental Health Sciences). It addresses the sharply rising demand from environmental protection agencies, chemical industries and NGOs to use models in order to screen the impact of chemicals released in the environment.

Course description:
This 3-hour (every Thursday, 3-6pm) advanced course covers a comprehensive set of tools for risk modeling of chemicals, from emissions into environmental compartments, mass in the environment, intake by humans, mass in the human body and effects on human health.  The course will first address steady-state multi-media modeling, exposure modeling, and pharmacokinetic modeling. It will then expand the theory to dynamic modeling, using diagnostic tools such as interpretation of eigenvalues and eigenvectors of matrix-formulated differential equations. Finally, the course will address the risk linked to bacteria propagation and infectious diseases and give insights on uncertainty propagation in risk modeling.

This course will use a hands on approach, starting from a series of problems to solve, discussing what type of information is needed, and experimenting with using and interpreting models to provide additional understanding and possible solutions, bearing in mind that "All models are wrong, but some are useful."