Dynamic Strategies for Mitigating Societal Risk of Avian Influenza Pandemic Outbreaks

Date: Oct 18
Time: 1:00 p.m.
Place: 202 Dunstan Hall

Dr. Tapas DasDr. Tapas Das
Professor
Department of Industrial and Management System Engineering
University of South Florida

Dr. Tapas K. Das is a Professor with interests in applied stochastic processes, quality engineering, and dynamic decision processes. Current research includes simulation based optimization of competitive and noncompetitive decision processes.

Abstract

Dynamic Strategies for Mitigating Societal Risk of Avian Influenza Pandemic Outbreaks
Most epidemiologists believe that a human-to-human transmittable avian influenza pandemic is impending. In such an event, as many as 90 million people in the US are expected to become ill and need assistance. The Centers for Disease Control (CDC) and the Department of Health and Human Services (HHS) strongly emphasize the need for effective strategies for mitigating pandemic outbreaks. We are developing mitigation strategies applicable at two levels: national and local. The national strategy must allocate limited federal resources including vaccine, antiviral drugs, mobile health care facilities, and personnel to the affected areas. The strategy at the local level must guide mitigation decisions for vaccination, prophylaxis, hospitalization, and social distancing.

Improving Accuracy of Micro-arrays and Use Gene Expression Patterns for Efficient Prostate Cancer Characterization and Treatment Strategy Development

Date: Oct 18
Time: 1:00 p.m.
Place: 202 Dunstan Hall

Abstract

Improving Accuracy of Micro-arrays and Use Gene Expression Patterns for Efficient Prostate Cancer Characterization and Treatment Strategy Development
Microarrays, a technology that measures the expression levels of genes in human cells, is a significant tool for disease diagnosis and drug discovery. However, errors inherent in the microarray technology, which tend to distort the gene expression values by imparting noise, have been a major obstacle in meeting the high expectations. We are developing a novel approach for denoising 2-D microarray images. The method considers the special characteristics of microarray images and uses a recently developed tool of mathematics known as Dual Tree Complex Wavelet Transform (DT-CWT).

It is well known that 64% of men between 60-70 years of age have prostatic carcinomas, out of which 16.6 % will develop prostate cancer and 3.33% develop metastasis leading to death. Currently, a large percentage of men with prostatic carcinomas are being treated who could be much better off without treatment. Hence, it is critical to determine which types of carcinomas are likely to progress to metastasis and hence be treated. We are working toward developing gene expression based strategies in characterizing prostatic carcinomas and developing corresponding treatment needs.