William A. Thompson, Assistant Professor (Research), Division of Applied Mathematics, Brown Univ.
Andy Martwick, Assistant Professor, Department of Physics, Portland State University
Joel K. Weltman, a Clinical Professor Emeritus of Medicine in the Department of Medicine, Alpert Medical School, Brown University
As reported by CNN in October 2009, the declaration of the H1N1 swine flu pandemic as a national emergency in the USA highlights the magnitude and continuing spread of the first pandemic flu outbreak in forty years. The H1N1 swine flu pandemic that began in March 2009 is the most recent outbreak of influenza A to threaten the human species. Type A influenza viruses, including the H1N1 of the current pandemic, are the cause of the most frequent and most serious influenza infections in humans.
In this article, we discuss how signal processing techniques can be used to analyze the information content of H1N1 genomic sequences, which could help in understanding this and future flu outbreaks. We first explain how the genetic code is used by the influenza virus to encode the information that is essential to viral function. Next, we demonstrate how the digital signal processing tools of decimation, periodicity, and integration are used to reveal the patterns of entropic uncertainty of that information. We propose that analysis of these patterns changing over time and space can give insight into mechanisms of regional influenza epidemics and global influenza pandemics that may help provide a basis for design of counter measures.