Assessing North American Influenza Dynamics with Hierarchical Spatio-Temporal Models

• Activity Number: 536
• Type: Contributed
• Date/Time: Wednesday, August 4, 2010 : 10:30 AM to 12:20 PM
• Sponsor: Section on Bayesian Statistical Science
• Author(s): Jessica Anderson*+ and Mevin B. Hooten and Lance Waller
• Companies: Utah State University and Utah State University and Emory University
• Keywords: Areal Data ; Dynamical Model ; Epidemiology

Abstract

We present a general statistical modeling framework to characterize continental-level influenza dynamics in the United States for the purposes of examining state-level epidemiological sources and sinks. The methods we describe depend directly on state-level influenza data that are updated weekly and available on the internet. Advances in search engine query analysis have provided powerful new tools for collecting epidemiological data and, when used in conjunction with sophisticated statistical models, allow for the identification and quantification of the flow of influenza across the continental United States. Our proposed methods, when conditioned on this comprehensive search query product, can provide unprecedented scientific learning about large-scale pathways and barriers to disease transmission which can ultimately be helpful for policy, remediation, and response efforts.