Seasonal influenza epidemics offer unique opportunities to study the invasion and re-invasion waves of a pathogen in a partially immune population. Detailed patterns of spread remain elusive, however, due to lack of granular disease data. Here we model high-volume city-level medical claims data and human mobility proxies to explore the drivers of influenza spread in the US during 2002-2010. Although the speed and pathways of spread varied across seasons, seven of eight epidemics likely originated in the Southern US. Each epidemic was associated with 1-5 early long-range transmission events, half of which sparked onward transmission. Gravity model estimates indicate a sharp decay in influenza transmission with the distance between infectious and susceptible cities, consistent with spread dominated by work commutes rather than air traffic. Two early-onset seasons associated with antigenic novelty had particularly localized modes of spread, suggesting that novel strains may spread in a more localized fashion than previously anticipated.

Abstract Summary: SNOMAD is a collection of algorithms for the normalization and standardization of gene expression datasets derived from diverse biological and technological sources. In addition to conventional transformations and visualization tools, SNOMAD includes two non-linear transformations which correct for bias and variance which are non-uniformly distributed across the range of microarray element signal intensities: (1) Local mean normalization; and (2) Local variance correction (Z-score generation using a locally calculated standard deviation). Availability: The SNOMAD tools were developed in the R statistical language http://www.r-project.org/. SNOMAD is an interactive, user-friendly web-application which can be accessed freely via the internet with any standard HTML browser: http://pevsnerlab.kennedykrieger.org/snomad.htm. Contact: [email protected] or [email protected] * To whom correspondence should be addressed. † Present address: Wadham College, Oxford University, UK.