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ABSTRACT: Background
Data about influenza mortality burden in northern China are limited. This study estimated mortality burden in Beijing associated with seasonal influenza from 2007 to 2013 and the 2009 H1N1 pandemic.Methods
We estimated influenza-associated excess mortality by fitting a negative binomial model using weekly mortality data as the outcome of interest with the percent of influenza-positive samples by type/subtype as predictor variables.Results
From 2007 to 2013, an average of 2375 (CI 1002-8688) deaths was attributed to influenza per season, accounting for 3% of all deaths. Overall, 81% of the deaths attributed to influenza occurred in adults aged ?65 years, and the influenza-associated mortality rate in this age group was higher than the rate among those aged <65 years (113.6 [CI 49.5-397.4] versus 4.4 [CI 1.7-18.6] per 100 000, P < .05). The mortality rate associated with the 2009 H1N1 pandemic in 2009/2010 was comparable to that of seasonal influenza during the seasonal years (19.9 [CI 10.4-33.1] vs 17.2 [CI 7.2-67.5] per 100 000). People aged <65 years represented a greater proportion of all deaths during the influenza A(H1N1)pdm09 pandemic period than during the seasonal epidemics (27.0% vs 17.7%, P < .05).Conclusions
Influenza is an important contributor to mortality in Beijing, especially among those aged ?65 years. These results support current policies to give priority to older adults for seasonal influenza vaccination and help to define the populations at highest risk for death that could be targeted for pandemic influenza vaccination.
SUBMITTER: Wu S
PROVIDER: S-EPMC5818349 | biostudies-literature | 2018 Jan
REPOSITORIES: biostudies-literature
Influenza and other respiratory viruses 20171202 1
<h4>Background</h4>Data about influenza mortality burden in northern China are limited. This study estimated mortality burden in Beijing associated with seasonal influenza from 2007 to 2013 and the 2009 H1N1 pandemic.<h4>Methods</h4>We estimated influenza-associated excess mortality by fitting a negative binomial model using weekly mortality data as the outcome of interest with the percent of influenza-positive samples by type/subtype as predictor variables.<h4>Results</h4>From 2007 to 2013, an ...[more]