A Bayesian Approach to Characterize Hong Kong Influenza Surveillance Systems
DOI:
https://doi.org/10.5210/ojphi.v5i1.4567Abstract
To develop a statistical tool for characterizing multiple influenza surveillance data for situational awareness, we used Bayesian statistical model incorporating factors such as disease transmission, behavior patterns in healthcare seeking and provision, biases and errors embedded in the reporting process, with the observed data from Hong Kong. The patterns in the ratios of paired data streams help to characterize influenza surveillance systems. To better interpret influenza surveillance data, behavior data related to healthcare resources utilization need to be collected in real-time.Published
2013-03-24
How to Cite
Zhang, Y., Arab, A., & Stoto, M. A. (2013). A Bayesian Approach to Characterize Hong Kong Influenza Surveillance Systems. Online Journal of Public Health Informatics, 5(1). https://doi.org/10.5210/ojphi.v5i1.4567
Issue
Section
Poster Presentations