We employed multiple time series analysis to estimate the impact of influenza on mortality in different age groups, using a procedure for updating estimates as current data become available from national mortality data collected from 1962 to 1983. We compared mortality estimates that resulted from a multivariate model for epidemic forecasting with those obtained from univariate models. We found more accurate prediction of deaths from all age groups using the multivarate model. While the univariate models show an adequate fit to the data, the multivariate model often enables earlier detection of epidemics. Additionally, the multivariate approach provides insight into relationships among different age groups at different points in time. For both models, the largest excess mortality due to pneumonia and influenza during influenza epidemics occurred among those 65 years of age and older. Although multiple time series models appear useful in epidemiologic analysis, the complexity of the modelling process may limit routine application.