1887
Research articles Open Access
Like 0

Abstract

Reliable estimates of the morbidity burden caused by the 2009 pandemic influenza (pH1N1) are important for assessing the severity of the pandemic. Poisson regression models were fitted to weekly numbers of cause-specific hospitalisation in Hong Kong from 2005 to 2010. Excess hospitalisation associated with the 2009 pandemic and seasonal influenza was derived from the model by incorporating the proxy variables of weekly proportions of specimens positive for the pandemic influenza A(H1N1)pdm09, seasonal influenza A (subtypes H3N2 and H1N1) and B viruses. Compared with seasonal influenza, pH1N1 influenza was associated with higher hospitalisation rates for acute respiratory disease (ARD) among children younger than 18 years and adults aged between 18 and 64 years, but among the elderly aged 65 years and older the hospitalisation rates were lower for pH1N1 than for seasonal H3N2 and H1N1 influenza. Hospitalisation rates for chronic diseases associated with pH1N1 influenza were generally higher than those associated with seasonal influenza. The reported hospitalised cases with laboratory-confirmed pandemic infections accounted for only 16% of pH1N1 influenza-associated hospitalisations for ARD in the age group 75 years and older, and 5?66% of hospitalisations for chronic diseases in those older than 40 years. The 2009 H1N1 influenza pandemic was associated with a dramatically increased risk of hospitalisation among children and young adults. The morbidity burden of pandemic was underreported in old people and in those with chronic conditions.

Loading

Article metrics loading...

/content/10.2807/ese.17.45.20309-en
2012-11-08
2017-12-18
http://instance.metastore.ingenta.com/content/10.2807/ese.17.45.20309-en
Loading
Loading full text...

Full text loading...

/deliver/fulltext/eurosurveillance/17/45/art20309-en.htm?itemId=/content/10.2807/ese.17.45.20309-en&mimeType=html&fmt=ahah
Comment has been disabled for this content
Submit comment
Close
Comment moderation successfully completed
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error