lecture image Frontiers of Scientific Computing Lecture Series
Simple Mathematical Models Can Provide New Insights into Stopping Epidemics
James (Mac) Hyman, Tulane University
Johnston Hall 338
April 25, 2011 - 03:30 pm
Public health workers are reaching out to mathematical scientists to use disease models to understand, and mitigate, the spread of emerging diseases. Mathematical and computational scientists are needed to create new tools that can anticipate the spread of new diseases and evaluate the effectiveness of different approaches for bringing epidemics under control. Simple epidemic models can be used in the classroom to provide insight into how mathematical sciences can improve the health of our world and save lives. The talk will provide an overview, for general audiences, of what type of insights these models can provide. I will describe some of the mathematical advances needed to create the next generation of models, and share my personal experiences in controlling the spread of HIV/AIDS, SARS, malaria, foot and mouth disease, and the novel H1N1 (swine) flu.
Speaker's Bio:
Mac Hyman returned to Tulane University after leading the Mathematical Modeling and Analysis Group at Los Alamos National Laboratory for over twenty years. He is the past president of the Society for Industrial and Applied Mathematics (SIAM) and a Fellow of SIAM and the AAAS. He has has over 200 scientific publications and edited 9 books in topics ranging from mathematical biology, nonlinear dynamical systems, and the numerical solution of differential equations. When away from his day job, he creates ceramic sculptures, is a dancer, plays (at) the piano, and spends as much time as he can skiing off the top of mountains in northern New Mexico. My research interests include building a solid mathematical foundation for difference approximations to partial differential equations and using mathematical models to better understand and predict the spread of epidemics. Most of my publications are in mathematical modeling and I have passion for writing quality software for numerical differentiation, interface tracking, adaptive grid generation, and the iterative solutions of nonlinear systems.