Population Dynamics in the Elderly: The Need for Age-Adjustment in National BioSurveillance Systems

  • Steven A. Cohen
  • Elena N. Naumova
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4506)


With the growing threat of pandemic influenza, efforts to improve national surveillance to better predict and prevent this disease from affecting the most vulnerable populations are being undertaken. This paper examines the utility of Medicare data to obtain age-specific influenza hospitalization rates for historical analyses. We present a novel approach to describing and analyzing age-specific patterns of hospitalizations using Medicare data and show the implications of a dynamic population age distribution on hospitalization rates. We use these techniques to highlight the utility of implementing a real-time nationwide surveillance system for influenza cases and vaccination, and discuss opportunities to improve the existing system to inform policy and reduce the burden of influenza nationwide.


real-time surveillance influenza age-adjustment  elderly Medicare 


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  1. 1.
    Farley, D.O., et al.: Trends in Special Medicare Payments and Service Utilization for Rural Areas in the 1990s. RAND (June 2002)Google Scholar
  2. 2.
    Horiuchi, S., et al.: Differential Patterns of Age-related Mortality Increase in Middle Age and Old Age. J. Gerontol. A Biol. Sci. Med. Sci. 58, 495–507 (2003)Google Scholar
  3. 3.
    Jefferson, T., et al.: Efficacy and Effectiveness of Influenza Vaccines in Elderly People: A Systematic Review. Lancet 366, 1165–1174 (2005)CrossRefGoogle Scholar
  4. 4.
    McElhany, J.E.: Influenza: A Preventable Lethal Disease. J. Gerontol. A Biol. Sci. Med. Sci. 57, M627–M628 (2002)Google Scholar
  5. 5.
    Meltzer, M.I., Cox, N.J., Fukuda, K.: The Economic Impact of Pandemic Influenza in the United States: Priorities for Intervention. Emerg. Infect. Dis. 5, 659–671 (1999)Google Scholar
  6. 6.
    Muller, A.: Association between Income Inequality and Mortality among US States: Considering Population at Risk. Am. J. Public Health 96, 590–591 (2006)CrossRefGoogle Scholar
  7. 7.
    Naumova, E.N., et al.: The Spatiotemporal Dynamics of Influenza Hospitalizations in the United States Elderly. In preparationGoogle Scholar
  8. 8.
    Nichol, K.L., et al.: Effectiveness of Influenza Vaccine in the Elderly. Gerontology 42, 274–279 (1996)CrossRefGoogle Scholar
  9. 9.
    Piedra, P.A., et al.: Herd Immunity in Adults Against Influenza-related Illnesses with Use of the Trivalent-live Attenuated Influenza Vaccine (CAIV-T) in Children. Vaccine 23, 1540–1548 (2005)CrossRefGoogle Scholar
  10. 10.
    Reichert, T.A., et al.: The Japanese Experience with Vaccination Schoolchildren against Influenza. N. Engl. J. Med. 344, 889–896 (2001)CrossRefGoogle Scholar
  11. 11.
    Simonsen, L., et al.: Impact of Influenza Vaccination on Seasonal Mortality in the US Elderly Population. Arch. Intern. Med. 165, 265–272 (2005)CrossRefGoogle Scholar
  12. 12.
    Smith, N.M., et al.: Prevention and Control of Influenza: Recommendations of the Advisory Committee on Immunization Practices (ACIP). MMWR Recomm. Rep. 55, 1–42 (2006)Google Scholar
  13. 13.
    Thompson, W.W., et al.: Mortality Associated with Influenza and Respiratory Syncytial Virus in the United States. JAMA 289, 179–186 (2003)CrossRefGoogle Scholar
  14. 14.
    Thompson, W.W., et al.: Influenza-Associated Hospitalizations in the United States. JAMA 292, 1333–1340 (2004)CrossRefGoogle Scholar
  15. 15.
    US Census Bureau: American Community Survey Gulf Coast Area Data Profiles: Louisiana Data Profiles (2005), Accessed 3/12/07
  16. 16.
    Xu, K.T.: State-level Variations in Income-Related Inequality in Health and Health Achievement in the US. Soc. Sci. Med. 63, 457–464 (2006)CrossRefGoogle Scholar

Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Steven A. Cohen
    • 1
  • Elena N. Naumova
    • 2
  1. 1.Department of Population, Family, and Reproductive Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland 
  2. 2.Department of Public Health and Family Medicine, Tufts University School of Medicine, Boston, Massachusetts 

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