Background The total burden of influenza in primary care is difficult to assess. The case definition of medically attended “acute respiratory infection” (MAARI) in the German physician sentinel is sensitive; however, it requires modelling techniques to derive estimates of disease attributable to influenza. We aimed to examine the impact of type/subtype and age. Methods Data on MAARI and virological results of respiratory samples (virological sentinel) were available from 2001/02 until 2014/15. We constructed a generalized additive regression model for the periodic baseline and the secular trend. The weekly number of influenza‐positive samples represented influenza activity. In a second step, we distributed the estimated influenza‐attributable MAARI (iMAARI) according to the distribution of types/subtypes in the virological sentinel. Results Season‐specific iMAARI ranged from 0.7% to 8.9% of the population. Seasons with the strongest impact were dominated by A(H3), and iMAARI attack rate of the pandemic 2009 (A(H1)pdm09) was 4.9%. Regularly the two child age groups (0‐4 and 5‐14 years old) had the highest iMAARI attack rates reaching frequently levels up to 15%‐20%. Influenza B affected the age group of 5‐ to 14‐year‐old children substantially more than any other age group. Sensitivity analyses demonstrated both comparability and stability of the model. Conclusion We constructed a model that is well suited to estimate the substantial impact of influenza on the primary care sector. A(H3) causes overall the greatest number of iMAARI, and influenza B has the greatest impact on school‐age children. The model may incorporate time series of other pathogens as they become available.
【저자키워드】 Influenza, Germany, Burden of disease, Generalised additive model, medically attended acute respiratory illness, influenza type/subtype,