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There has long been interest in predicting influenza season onset and timing and magnitude of peak activity to guide initiation of efforts to produce vaccine, encourage and provide vaccination, and enable the healthcare system to prepare for the possible onslaught of those needing care, particularly hospitalization. It is a certainty that the seasonal influenza epidemic in the United States will occur annually and that influenza activity will begin to build up during the early winter months, usually starting in December. However, predicting the rate of build-up, timing, and intensity of peak activity has been difficult. Observing the rate of build-up, which influenza virus strains are circulating, and modeling based on past experience provide useful data and estimates, but these estimates, like weather predictions, are rarely reliable for very long to predict what will actually happen in the next weeks and months. Thus, any information that can add predictability to influenza season dynamics is of interest. In this vein, of high interest for pandemic influenza preparedness is understanding factors under human control that might predictably modify the dynamics and, thus, the trajectory of the seasonal influenza epidemic, delaying and lowering the magnitude of peak activity. In this issue of The Journal of Infectious Diseases, Ewing et al present 2 studies that add to our understanding and predictability of early influenza season dynamics [1]. Each study examined the effect of the Christmas–New Year holiday period on influenza season dynamics. The first is an analysis of observational data: influenza-like illness (ILI) visits over time as recorded in a national medical claims database managed by IMS Health [2] for each of 8 influenza seasons (2001–2009). The second is a series of models of influenza transmission in a synthetic population to examine the possible mechanisms behind the observed holiday decrease in influenza occurrence. For the first study, the authors found that the 2-week Christmas–New Year winter holiday period reduced visits for ILI and effectively delayed by at least 2 weeks the trajectory of what would be expected to happen had there been no holiday. The authors also noted a switch in relative ILI occurrence from children toward adults during the holiday period, a switch that gradually reversed after the holidays ended, and influenza occurrence began climbing again in all age groups. The models, testing several hypotheses for why ILI visits might be reduced, found that, indeed, holidays during which schools were closed resulted in reduced transmission and a delay in the trajectory of the buildup to peak influenza occurrence, whereas simply introducing a lot of holiday travel did not have this impact. The authors concluded that the Christmas–New Year holiday delays seasonal influenza epidemic peaks as a result of changes in contact patterns. The key dynamic appears to be the reduction in opportunities for children to transmit to each other and others as a result of the up to 2-week concurrent school holiday. These studies have some important strengths. The first used a national medical claims database (de-identified electronic CMS-1500 medical claim forms from full-time office-based active physicians throughout the United States) that captures almost 62% of outpatient visits in the United States, a database and influenza/ILI definition for which a high degree of correlation with US influenza activity independent of respiratory syncytial virus activity has been established [2]. Thus, it is specific for influenza. It examined 8 influenza seasons nationwide and demonstrated the same pattern of reduced medically attended ILI occurrence, after adjusting for reduced access to healthcare for all during the holiday period, with subsequent slow build-up after. Thus, the findings were consistent from year to year. The one exception was the 2003–2004 season that came early, peaked at the Christmas– New Year holiday, and rapidly declined without gradually “recovering” afterward. The models used were simple and clearly demonstrated the different impacts of school closure compared to travel on the build-up of influenza in the population, differences that made sense and, in the case of holiday school closures, were consistent with the observational findings. The studies add to and support the results of 2 other large observational studies at a national level in Argentina and E D I T O R I A L C O M M E N T A R Y

Christmas-New Year influenza lull: not too late for vaccination