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Improving the Estimation of Influenza-Related Mortality Over a Seasonal Baseline

Goldstein, Edwarda; Viboud, Cecileb; Charu, Vivekb,c; Lipsitch, Marca,d

doi: 10.1097/EDE.0b013e31826c2dda
Infectious diseases

Background: Existing methods for estimation of mortality attributable to influenza are limited by methodological and data uncertainty. We have used proxies for disease incidence of the three influenza cocirculating subtypes (A/H3N2, A/H1N1, and B) that combine data on influenza-like illness consultations and respiratory specimen testing to estimate influenza-associated mortality in the United States between 1997 and 2007.

Methods: Weekly mortality rate for several mortality causes potentially affected by influenza was regressed linearly against subtype-specific influenza incidence proxies, adjusting for temporal trend and seasonal baseline, modeled by periodic cubic splines.

Results: Average annual influenza-associated mortality rates per 100,000 individuals were estimated for the following underlying causes of death: for pneumonia and influenza, 1.73 (95% confidence interval = 1.53–1.93); for chronic lower respiratory disease, 1.70 (1.48–1.93); for all respiratory causes, 3.58 (3.04–4.14); for myocardial infarctions, 1.02 (0.85–1.2); for ischemic heart disease, 2.7 (2.23–3.16); for heart disease, 3.82 (3.21–4.4); for cerebrovascular deaths, 0.65 (0.51–0.78); for all circulatory causes, 4.6 (3.79–5.39); for cancer, 0.87 (0.68–1.05); for diabetes, 0.33 (0.26–0.39); for renal disease, 0.19 (0.14–0.24); for Alzheimer disease, 0.41 (0.3–0.52); and for all causes, 11.92 (10.17–13.67). For several underlying causes of death, baseline mortality rates changed after the introduction of the pneumococcal conjugate vaccine.

Conclusions: The proposed methodology establishes a linear relation between influenza incidence proxies and excess mortality, rendering temporally consistent model fits, and allowing for the assessment of related epidemiologic phenomena such as changes in mortality baselines.

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From the aDepartment of Epidemiology, Center for Communicable Disease Dynamics, Harvard School of Public Health, Boston, MA; bDivision of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, MD; cSchool of Medicine, Johns Hopkins University, Baltimore, MD; and dDepartment of Immunology and Infectious Diseases, Harvard School of Public Health, Boston, MA.

Submitted 7 November, 2011; accepted 22 March, 2012; posted 18 September 2012.

Supported, in part, by the US National Institutes of Health Models of Infectious Disease Agent Study program through cooperative agreement 1 U54 GM088558 (M.L., E.G.), by the US National Institutes of Health K01 award 1K01AI101010-01 (E.G.), and by the influenza research program of the Fogarty International Center, US NIH (C.V., V.C.).

The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of General Medical Sciences or the National Institutes of Health.

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Editors’ note: Related articles appear on pages 839 and 843.

Correspondence: Edward Goldstein, Harvard School of Public Health, Department of Epidemiology, 677 Huntington Ave, Kresge Room 506, Boston, MA 02115. E-mail:

© 2012 Lippincott Williams & Wilkins, Inc.