269363 Wrapping up: Different approaches for different questions

Saturday, October 27, 2012 : 3:30 PM - 4:00 PM

Nina Fefferman, PhD , Center for Discrete Mathematics and Theoretical Computer Science, Rutgers University, Piscataway, NJ
As the capstone of the institute, this presentation will summarize the potential uses of mathematical models in answering questions of public health interest, and touch on some of the common themes present between model types, and the major contracts between them. There will also be time to address any remaining questions from participants before the institute concludes.

Learning Areas:
Basic medical science applied in public health
Epidemiology
Other professions or practice related to public health
Protection of the public in relation to communicable diseases including prevention or control
Public health or related research
Systems thinking models (conceptual and theoretical models), applications related to public health

Learning Objectives:
1. Describe the difference between compartmental, network and agent-based models. 2. Evaluate which type of model may be most appropriate for the participant's research goals. 3. Identify next-steps and areas of further interest.

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I am qualified to present the proposed topic because I am an experienced infectious disease modeler, with faculty appointments at Rutgers University in the Department of Ecology, Evolution and Natural Resources, as well as the Center for Discrete Math and Theoretical Computer Science. Additionally, I have extensive experience teaching mathematical modeling in a graduate and professional school setting.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.

Back to: 1004.0: A gentle introduction to mathematical modeling: Lessons from the living dead