Estimating Influenza-Related Hospital Admissions in Children and Adults: A Time Series Analysis
Introduction: Influenza is associated with illnesses such as pneumonia and other respiratory conditions and in severe cases leads to death. The prevalence of these illnesses and deaths fluctuates with the seasons during the year, even in the absence of influenza. Although many studies have focussed on mortality associated with influenza epidemics, and some have examined hospitalizations in elderly patients, there are very few studies that have examined the effect of influenza epidemics on adults or children. This study seeks to determine the association between general practitioner (GP) consultations for influenza-like illnesses and hospital admissions of adults and children associated with influenza epidemics. Methods: Structural Time Series Models with stochastic trend and seasonal components were developed for two age groups (children aged 0-15 years, and adults aged 16-50 years). Data from the Swiss Sentinel Surveillance Network on GP consultation rates for influenza-like illnesses, and data from Swiss hospital admissions, were obtained for the period 1987-1996. The explanatory variables (i.e., the percentage of GP consultations for influenza-like illnesses and a 1-week lag of this variable) were modeled against hospital admission rates for pneumonia and influenza and other respiratory conditions. Excess hospitalizations were calculated as the difference between predicted hospital admissions during influenza epidemics and expected hospital admissions in the absence of influenza epidemics. Results: In these two age groups, there was an annual average of 1452 (range: 1000-1700) hospital admissions directly associated with influenza epidemics. Excess admission rates were substantially higher in children (pneumonia and influenza: 4.77 per 10 000 children per year, and other respiratory conditions: 2.29 per 10 000 children per year) compared with adults (pneumonia and influenza: 0.86 per 10 000 adults per year and other respiratory conditions: 0.68 per 10 000 adults per year). The models explained 56-84% of the variation in hospital admissions. The seasonal patterns were stable over the 10 years modeled and the variances of the trends were small. Conclusion: The structural time series models is an ideal approach to model influenza-related hospitalizations as the models capture trends, seasonal variation, and the association with exogenous factors.
Disease Management and Health Outcomes
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