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Local Variations in Spatial Synchrony of Influenza Epidemics

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Listed:
  • James H Stark
  • Derek A T Cummings
  • Bard Ermentrout
  • Stephen Ostroff
  • Ravi Sharma
  • Samuel Stebbins
  • Donald S Burke
  • Stephen R Wisniewski

Abstract

Background: Understanding the mechanism of influenza spread across multiple geographic scales is not complete. While the mechanism of dissemination across regions and states of the United States has been described, understanding the determinants of dissemination between counties has not been elucidated. The paucity of high resolution spatial-temporal influenza incidence data to evaluate disease structure is often not available. Methodology and Findings: We report on the underlying relationship between the spread of influenza and human movement between counties of one state. Significant synchrony in the timing of epidemics exists across the entire state and decay with distance (regional correlation = 62%). Synchrony as a function of population size display evidence of hierarchical spread with more synchronized epidemics occurring among the most populated counties. A gravity model describing movement between two populations is a stronger predictor of influenza spread than adult movement to and from workplaces suggesting that non-routine and leisure travel drive local epidemics. Conclusions: These findings highlight the complex nature of influenza spread across multiple geographic scales.

Suggested Citation

  • James H Stark & Derek A T Cummings & Bard Ermentrout & Stephen Ostroff & Ravi Sharma & Samuel Stebbins & Donald S Burke & Stephen R Wisniewski, 2012. "Local Variations in Spatial Synchrony of Influenza Epidemics," PLOS ONE, Public Library of Science, vol. 7(8), pages 1-9, August.
    • Handle: RePEc:plo:pone00:0043528
    DOI: 10.1371/journal.pone.0043528
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    References listed on IDEAS

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    1. Elizabeth C Lee & Ali Arab & Sandra M Goldlust & Cécile Viboud & Bryan T Grenfell & Shweta Bansal, 2018. "Deploying digital health data to optimize influenza surveillance at national and local scales," PLOS Computational Biology, Public Library of Science, vol. 14(3), pages 1-23, March.

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