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

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.