American Journal of Epidemiology Advance Access originally published online on January 4, 2006
American Journal of Epidemiology 2006 163(4):316-326; doi:10.1093/aje/kwj040
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Original Contribution |
Patterns of Influenza-associated Mortality among US Elderly by Geographic Region and Virus Subtype, 1968–1998
1 Department of Epidemiology, University of Michigan, Ann Arbor, MI
2 Department of Statistics, University of Michigan, Ann Arbor, MI
Correspondence to Dr. Sharon K. Greene, Foodborne and Diarrheal Diseases Branch, Centers for Disease Control and Prevention, 1600 Clifton Road, Mailstop A-38, Atlanta, GA 30033 (e-mail: SGreene1{at}cdc.gov).
The regular seasonality of influenza in temperate countries is recognized, but regional differences in patterns of influenza-related mortality are poorly understood. Identifying patterns could improve epidemic prediction and prevention. The authors analyzed the monthly percentage of deaths attributable to pneumonia and influenza among people aged 65 or more years in the contiguous United States, 1968–1998. The local Moran's I test for spatial autocorrelation and correlograms assessing space-time synchrony within each influenza season were applied to detect and to characterize mortality patterns. Western US regions experienced epidemics of greater magnitude than did eastern regions. Positive spatial autocorrelation (two-sided p = 0.001) revealed the similarity in influenza mortality of neighboring states, with several western states forming a focus of high mortality. In transmission seasons dominated by virus subtype A(H3N2), mortality was correlated at a high and consistent level across the United States (mean correlation = 0.56, standard deviation = 0.134). However, when subtype A(H1N1) or type B dominated, the average synchrony was lower (mean correlation = 0.23, standard deviation = 0.058). These novel analyses suggest that causes of spatial heterogeneity (e.g., large-scale environmental drivers and population movement) have impacted influenza-associated mortality.
climate; communicable diseases; environment and public health; influenza; mortality; National Center for Health Statistics (U.S.); space-time clustering
Abbreviations: ICD, International Classification of Diseases; NCDC, National Climatic Data Center; SD, standard deviation; STIS, Space-Time Intelligence System
CiteULike 
Connotea 
Del.icio.us What's this?
This article has been cited by other articles:
|
|
 |
|
  P. Crepey and M. Barthelemy Detecting Robust Patterns in the Spread of Epidemics: A Case Study of Influenza in the United States and France Am. J. Epidemiol., December 1, 2007; 166(11): 1244 - 1251. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 J. D. Treanor Influenza -- The Goal of Control N. Engl. J. Med., October 4, 2007; 357(14): 1439 - 1441. [Full Text] [PDF]
|
|
|
|
 |
|
 K. Koelle, S. Cobey, B. Grenfell, and M. Pascual Epochal Evolution Shapes the Phylodynamics of Interpandemic Influenza A (H3N2) in Humans Science, December 22, 2006; 314(5807): 1898 - 1903. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
C. Viboud, O. N. Bjornstad, D. L. Smith, L. Simonsen, M. A. Miller, and B. T. Grenfell Synchrony, Waves, and Spatial Hierarchies in the Spread of Influenza Science, April 21, 2006; 312(5772): 447 - 451. [Abstract] [Full Text] [PDF]
|
|