Characterizing Influenza surveillance systems performance: application of a Bayesian hierarchical statistical model to Hong Kong surveillance data.

ABSTRACT:

Background

Infectious disease surveillance is a process the product of which reflects both actual disease trends and public awareness of the disease. Decisions made by patients, health care providers, and public health professionals about seeking and providing health care and about reporting cases to health authorities are all influenced by the information environment, which changes constantly. Biases are therefore imbedded in surveillance systems; these biases need to be characterized to provide better situational awareness for decision-making purposes. Our goal is to develop a statistical framework to characterize influenza surveillance systems, particularly their correlation with the information environment.

Methods

We identified Hong Kong influenza surveillance data syst

SUBMITTER: Zhang Y 

PROVIDER: S-EPMC4246552 | biostudies-literature | 2014 Aug

REPOSITORIES: biostudies-literature