
4:00pm to 5:00pm |
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GBCB Seminar--Genetics, Bioinformatics & Computational Biology
(Seminar/Conference)
Speaker: Bryan L Lewis, PhD candidate in GBCB
http://ndssl.vbi.vt.edu/people/blewis.html
Advisor: Dr. Chris Barrett, Director of Network Dynamics & Simulation Science Laboratory
http://ndssl.vbi.vt.edu/
http://ndssl.vbi.vt.edu/people/cbarrett.html
Title:
in silico Epidemiology: Computer Simulations for Public Health Research
Public Health is one of the most compelling and important challenges faced by humankind. Advances in medicine have vastly improved our ability to identify and cure illnesses, however, many diseases continue to cause significant morbidity and mortality worldwide. Emerging diseases (SARS, pandemic influenza, and XDR TB for example) for which effective medicines have yet to be developed also pose a serious threat to the public's health. The field of Computational Epidemiology tackles public health problems by coupling the power of recently developed simulation tools with public health knowledge and methods developed by epidemiologists over the years. Simulations that combine realistic populations, their behaviors, disease propagation, and public health policies offer a unique opportunity to run public health experiments in silico. For public policy decision-makers this affords the ability to manipulate and gain an intuition about the policies they are considering. For public health researchers these simulations can provide a wealth of information that would be unobtainable in the real world, allowing deep and novel analyses of public health data. Fully understanding and interpreting the complexity represented in these simulations is challenging and is an active area of research in complexity science. The results of several experiments will be presented covering a range of modeling techniques and analytic methods. The first set of experiments explores the general behavior and sensitivity of these systems. The second set demonstrates how having detailed representations can lead to novel analyses and experimental designs. A third set describes methods developed to further understand the co-evolution of a population's social network resulting from behavior changes stimulated by and infectious disease epidemic. These are simple examples of the contributions in silico epidemiology can make to public health research.
Refreshments from 3:15-3:55, seminar starts promptly at 4pm.
Open to the public, your attendance is welcome!! More information...
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