Meeting the threat of infectious diseases with statistical models: Influenza as a case study
Monday, November 4, 2013: 10:30 a.m. - 12:00 p.m.
Infectious diseases pose a significant public health threat to the developing world as well as industrialized nations. Influenza is a particularly notorious example due to its global impact, rapid spread, constant evolution, and connection with many other illnesses. Additionally, the ongoing threat of a severe pandemic, such as that seen in 1918, adds greater uncertainty and urgency to better characterize the epidemiology of this illness. Statisticians are playing an increasingly important role in understanding and responding to the threat of influenza and other infectious diseases. The work of the statistician is to derive novel approaches to understanding disease dynamics and determine how to best use existing data to answer pressing questions related to the control of infectious diseases.
This session will highlight the work of three researchers who are involved in important work in understanding the transmissibility and dynamics of influenza. Their work has far-reaching implications for developing policies that are effective in preparing for and responding to influenza outbreaks. The methods presented are also applicable for other infectious diseases, including new and emerging illnesses, such as was witnessed in the 2002-2003 SARS outbreak.
Session Objectives: Demonstrate the use of statistical methods in the study of infectious diseases.
See individual abstracts for presenting author's disclosure statement and author's information.
Organized by: Applied Public Health Statistics
Endorsed by: Epidemiology
Medical (CME), Health Education (CHES), Nursing (CNE), Public Health (CPH)
Masters Certified Health Education Specialist (MCHES)