Estimating infection attack rates and severity in real time during an influenza pandemic: analysis of serial cross-sectional serologic surveillance data.
In an emerging influenza pandemic, estimating severity (the probability of a severe outcome, such as hospitalization, if infected) is a public health priority. As many influenza infections are subclinical, sero-surveillance is needed to allow reliable real-time estimates of infection attack rate (IA...
Main Authors: | Joseph T Wu, Andrew Ho, Edward S K Ma, Cheuk Kwong Lee, Daniel K W Chu, Po-Lai Ho, Ivan F N Hung, Lai Ming Ho, Che Kit Lin, Thomas Tsang, Su-Vui Lo, Yu-Lung Lau, Gabriel M Leung, Benjamin J Cowling, J S Malik Peiris |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2011-10-01
|
Series: | PLoS Medicine |
Online Access: | http://europepmc.org/articles/PMC3186812?pdf=render |
Similar Items
-
Inferring influenza infection attack rate from seroprevalence data.
by: Joseph T Wu, et al.
Published: (2014-04-01) -
Optimizing Use of Multistream Influenza Sentinel Surveillance Data
by: Eric H. Y. Lau, et al.
Published: (2008-07-01) -
Digital Dashboard Design Using Multiple Data Streams for Disease Surveillance With Influenza Surveillance as an Example
by: Cheng, Calvin KY, et al.
Published: (2011-10-01) -
Electronic School Absenteeism Monitoring and Influenza Surveillance, Hong Kong
by: Calvin K.Y. Cheng, et al.
Published: (2012-05-01) -
Harnessing the potential of blood donation archives for influenza surveillance and control.
by: Yanyu Zhang, et al.
Published: (2020-01-01)