Abstract
The 2009 H1N1 influenza pandemic provides a unique opportunity for detailed examination of the spatial dynamics of an emerging pathogen. In the US, the pandemic was characterized by substantial geographical heterogeneity: the 2009 spring wave was limited mainly to northeastern cities while the larger fall wave affected the whole country. Here we use finely resolved spatial and temporal influenza disease data based on electronic medical claims to explore the spread of the fall pandemic wave across 271 US cities and associated suburban areas. We document a clear spatial pattern in the timing of onset of the fall wave, starting in southeastern cities and spreading outwards over a period of three months. We use mechanistic models to tease apart the external factors associated with the timing of the fall wave arrival: differential seeding events linked to demographic factors, school opening dates, absolute humidity, prior immunity from the spring wave, spatial diffusion, and their interactions. Although the onset of the fall wave was correlated with school openings as previously reported, models including spatial spread alone resulted in better fit. The best model had a combination of the two. Absolute humidity or prior exposure during the spring wave did not improve the fit and population size only played a weak role. In conclusion, the protracted spread of pandemic influenza in fall 2009 in the US was dominated by short-distance spatial spread partially catalysed by school openings rather than long-distance transmission events. This is in contrast to the rapid hierarchical transmission patterns previously described for seasonal influenza. The findings underline the critical role that school-age children play in facilitating the geographic spread of pandemic influenza and highlight the need for further information on the movement and mixing patterns of this age group.
Highlights
Understanding the spatio-temporal spread of infectious disease is important both for design of control strategies and to deepen fundamental knowledge about the interaction between epidemic dynamics and spatial mixing of the host population
We used physician diagnoses codes to generate a dataset of the weekly number of office visits with diagnosed influenza-like illness for 271 US locations
Its onset in the South Eastern US precipitated a slow radial spread that took 3 months to diffuse across the country. These patterns were replicated by models that included short-distance spatial transmission between nearby locations and increased transmission rates when school was in session
Summary
Understanding the spatio-temporal spread of infectious disease is important both for design of control strategies and to deepen fundamental knowledge about the interaction between epidemic dynamics and spatial mixing of the host population. Previous efforts have sought to forecast the likely spatial spread of pandemic influenza with model simulations accounting for intricate host demography and mixing data [10,20]. While mortality records were useful to explore the spatial transmission of the devastating 1918 pandemic in the US and UK [5], such data typically lack power to investigate disease patterns in small geographical areas or during more recent and milder seasons. Increased disease surveillance and data availability in the context of the 2009 A/H1N1pdm pandemic provides a unique opportunity to explore the spatial spread of influenza in more detail, identify further data gaps, and validate existing models and theory. We used a rich dataset of influenza-like-illness records compiled from electronic medical claims and covering about 50% of outpatient physician visits in 2009 across the US to study influenza spread with an unprece-
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