tetano
Editor, Senior Moderator
Citation: Stark JH, Cummings DAT, Ermentrout B, Ostroff S, Sharma R, et al. (2012) Local Variations in Spatial Synchrony of Influenza Epidemics. PLoS ONE 7(8): e43528. doi:10.1371/journal.pone.0043528
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.
http://www.plosone.org/article/fetc...icleURI=info:doi/10.1371/journal.pone.0043528
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.
http://www.plosone.org/article/fetc...icleURI=info:doi/10.1371/journal.pone.0043528