Controlling Pandemic Influenza: Uses of Stochastic Simulation and Estimation Models

Ira M. Longini, Jr., Professor, Program of Biostatistics and Biomathematics, Hutchinson Research Center and Department of Biostatistics, School of Public Health and Community Medicine, University of Washington

The world appears to be on the brink of a deadly influenza pandemic. Recent human deaths due to infection by highly pathogenic avian influenza A (H5N1) virus have raised the specter of a devastating pandemic like that of 1917–1918, should this avian virus evolve to become readily transmissible among humans. It is optimal to contain a nascent strain of influenza at the source. If this fails, then the best strategy is to slow spread until a well-matched vaccine can be made and distributed. In this talk, I describe stochastic simulation and estimation models to investigate the spread of a pandemic strain of influenza virus both at the source and throughout the US. I will present real-time statistical estimation methods to be used at the source of an expanding initial cluster of a potential pandemic influenza strain. I will then show how these initial estimates can be used to model the impact that a variety of levels and combinations of influenza antiviral agents, vaccines, and modified social have on the timing and magnitude of this spread.

The P/T Colloquium is
typically held each
Thursday, 3:45–5:00 PM.

Collaborations 3:15 PM.