1887
Research articles Open Access
Like 0

Abstract

Assessing the severity of emerging infections is challenging because of potential biases in case ascertainment. The first human case of infection with influenza A(H7N9) virus was identified in China in March 2013; since then, the virus has caused two epidemic waves in the country. There were 134 laboratory-confirmed cases detected in the first epidemic wave from January to September 2013. In the second epidemic wave of human infections with avian influenza A(H7N9) virus in China from October 2013 to October 2014, we estimated that the risk of death among hospitalised cases of infection with influenza A(H7N9) virus was 48% (95% credibility interval: 42-54%), slightly higher than the corresponding risk in the first wave. Age-specific risks of death among hospitalised cases were also significantly higher in the second wave. Using data on symptomatic cases identified through national sentinel influenza-like illness surveillance, we estimated that the risk of death among symptomatic cases of infection with influenza A(H7N9) virus was 0.10% (95% credibility interval: 0.029-3.6%), which was similar to previous estimates for the first epidemic wave of human infections with influenza A(H7N9) virus in 2013. An increase in the risk of death among hospitalised cases in the second wave could be real because of changes in the virus, because of seasonal changes in host susceptibility to severe infection, or because of variation in treatment practices between hospitals, while the increase could be artefactual because of changes in ascertainment of cases in different areas at different times. .

Loading

Article metrics loading...

/content/10.2807/1560-7917.ES2014.19.49.20984
2014-12-11
2024-11-23
http://instance.metastore.ingenta.com/content/10.2807/1560-7917.ES2014.19.49.20984
Loading
Loading full text...

Full text loading...

/deliver/fulltext/eurosurveillance/19/49/art20984-en.htm?itemId=/content/10.2807/1560-7917.ES2014.19.49.20984&mimeType=html&fmt=ahah
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