Round Table: Ozgur M. Araz - Predictive Modeling and Decision Support for Managing Influenza
The College of IS&T Round Table presents:
Ozgur M. Araz, Ph.D.
College of Public Health
University of Nebraska Medical Center
Predictive Modeling and Decision Support for Managing Influenza
Friday, October 24th, 2014
11:30 a.m. to 1:00 p.m.
(Talk starts at noon.)
Pizza and sodas provided on a first-come, first-served basis.
Please RSVP to email@example.com.
Seasonal influenza epidemics are a major public health concern, causing three to five million cases of severe illness and about 250,000 to 500,000 deaths worldwide. These epidemics can be unpredictable and severe, therefore early detection of disease activity is important in reducing the public health impact. Early detection requires regular surveillance and most importantly reliable forecasting methods that can efficiently use surveillance data. In this presentation, first a dynamic linear model for predicting weekly hospitalizations due to influenza related illnesses in the state of Texas will be presented. Since hospitalization data are available with a six month to one year lag we use correlated temporal data as predictors, which are available in near real-time. Then, a stochastic optimization model will be described and analyzed for estimating medical resources, e.g., number of ventilators that the Texas Department of State Health Services and eight health service regions in the state should stockpile for a pandemic influenza under different severity scenarios.
Dr. Araz is an Assistant Professor in the College of Public Health at the University of Nebraska Medical Center. He received his Ph.D. degree from Arizona State University, MS degree from the State University of New York at Buffalo, and BS from Istanbul Technical University, all in Industrial Engineering. He currently teaches courses on Complex Systems Thinking, Strategic Systems Modeling and Social Dynamics and Agent Based Modeling. He previously taught Operations Management courses at the Red McCombs School of Business in the University of Texas at Austin where he also worked as a Postdoctoral Fellow in the Center for Computational Biology and Bioinformatics for one of the NIH MIDAS projects. He has published several peer reviewed articles in various journals including IIE Transactions on Healthcare Systems Engineering, Decision Support Systems, International Journal of Production Economics, PLOS One, Journal of Urban Health and Healthcare Management Science. His recent research has been in the field of complex systems modeling and simulation for understanding the spread of infectious diseases, and social dynamics of chronic diseases for public health prevention activities. He is a member of American Public Health Association, System Dynamics Society, INFORMS and Omega Rho-International Honor Society of Operations Research and Management Science.