Weibo Tang , Hao Lei , Nan Zhang , Yaojing Wang , Shimeng Cai , Shuyi Ji , Lei Yang , Mengya Yang , Can Chen , Shigui Yang , Dayan Wang , Yuelong Shu , RIDPHE Group
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引用次数: 0
Abstract
Background
China is an aging society, and the older population is at a higher risk of influenza infection and influenza-related mortality. However, there is limited knowledge regarding the aging of influenza epidemics, which is crucial for estimating the disease burden.
Methods
We collected weekly influenza surveillance data from 2005/06 to 2016/17, and quantified the aging of influenza-like illness (ILI) and influenza virus-positive cases in China via the mean age of the influenza cases and the proportion of individuals aged 65 and above among the influenza cases.
Results
On average, the mean age of ILI cases and influenza-positive cases increased by 0.52 years and 0.60 years per year, respectively, which is approximately three times the annual increase in the mean age of the population. Additionally, the proportion of individuals aged 65 and above among influenza-positive cases increased from 0.5% to 4.0%. The aging of patients infected with influenza B/Yamagata was the most rapid, with a mean age increase of 0.73 years per year, followed by those infected with influenza A (H1N1) and influenza A (H3N2). Conversely, there was no significant increase in the mean age of patients infected with influenza B/Victoria. The aging rate of influenza epidemics in southern China was significantly higher than in northern China.
Conclusions
Based on estimates of excess mortality due to influenza from 2010/11 to 2014/15, by 2050, the annual number of respiratory disease-related deaths associated with influenza is projected to increase 2.5-fold. This finding highlights the importance of influenza vaccination among older individuals in China.
期刊介绍:
Infectious Disease Modelling is an open access journal that undergoes peer-review. Its main objective is to facilitate research that combines mathematical modelling, retrieval and analysis of infection disease data, and public health decision support. The journal actively encourages original research that improves this interface, as well as review articles that highlight innovative methodologies relevant to data collection, informatics, and policy making in the field of public health.