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Estimation of influenza‐attributable medically attended acute respiratory illness by influenza type/subtype and age, Germany, 2001/02–2014/15

机译:2001 / 02-2014 / 15德国,按流感类型/亚型和年龄估算的归因于流感的医学护理急性呼吸道疾病

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Abstract BackgroundThe 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. MethodsData 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. ResultsSeason-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. ConclusionWe 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.
机译:摘要背景初级保健中流感的总负担难以评估。德国医师哨兵中医护人员“急性呼吸道感染”(MAARI)的病例定义很敏感;但是,它需要建模技术来得出可归因于流感的疾病的估计值。我们旨在研究类型/亚型和年龄的影响。方法从2001/02年至2014/15年可获得MAARI数据和呼吸道标本的病毒学结果(病毒前哨)。我们针对周期性基线和长期趋势构建了一个广义的加性回归模型。流感阳性样本的每周数量代表流感活动。在第二步中,我们根据病毒学前哨中类型/亚型的分布来分配估计的流感引起的MAARI(iMAARI)。结果特定季节的iMAARI占人口的0.7%至8.9%。影响最大的季节是A(H3),2009年大流行的iMAARI攻击率(A(H1)pdm09)为4.9%。通常,两个儿童年龄段(0-4和5-14岁)的iMAARI发作率最高,经常达到15%-20%。乙型流感对5至14岁儿童年龄段的影响比其他任何年龄段的影响大得多。敏感性分析表明该模型具有可比性和稳定性。结论我们构建了一个非常适合估算流感对初级保健部门的重大影响的模型。甲型(H3)导致iMAARI总数最多,乙型流感对学龄儿童的影响最大。该模型可能会合并其他病原体的时间序列。

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