This paper is in the following e-collection/theme issue:

Information System Evaluation and Best Practices (40) Theme Issue: Bayesian Methods In Medical Research (26) Use Cases in Human, Animal, and Zoonotic Communicable/Infectious Disease Surveillance (132) Influenza and Influenza-Like-Illness (ILI) Surveillance (219)

Published on in Vol 11, No 2 (2019):

The design and evaluation of a Bayesian system for detecting and characterizing outbreaks of influenza

The design and evaluation of a Bayesian system for detecting and characterizing outbreaks of influenza

The design and evaluation of a Bayesian system for detecting and characterizing outbreaks of influenza

Authors of this article:

Nicholas E. Millett1 ;   John M. Aronis1 ;   Michael M. Wagner1 ;   Fuchiang Tsui2 ;   Ye Ye1 ;   Jeffrey P. Ferraro3 ;   Peter J. Haug3 ;   Per Gesteland3 ;   Gregory F. Cooper1
The full text of this article is available as a PDF download by clicking here.
Article Authors Cited by Tweetations Metrics

    The prediction and characterization of outbreaks of infectious diseases such as influenza remains an open and important problem. This paper describes a framework for detecting and characterizing outbreaks of influenza and the results of testing it on data from ten outbreaks collected from two locations over five years. We model outbreaks with compartment models and expliccitly model non-influenza influenza-like illnesses.