Literature DB >> 31632600

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

Nicholas E Millett1, John M Aronis1, Michael M Wagner1, Fuchiang Tsui1, Ye Ye1, Jeffrey P Ferraro2, Peter J Haug2, Per H Gesteland2, Gregory F Cooper1.   

Abstract

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 explicitly model non-influenza influenza-like illnesses. This is an Open Access article. Authors own copyright of their articles appearing in the Journal of Public Health Informatics. Readers may copy articles without permission of the copyright owner(s), as long as the author and OJPHI are acknowledged in the copy and the copy is used for educational, not-for-profit purposes.

Entities:  

Year:  2019        PMID: 31632600      PMCID: PMC6788888          DOI: 10.5210/ojphi.v11i2.9952

Source DB:  PubMed          Journal:  Online J Public Health Inform        ISSN: 1947-2579


  12 in total

1.  How many illnesses does one emergency department visit represent? Using a population-based telephone survey to estimate the syndromic multiplier.

Authors:  Kristina B Metzger; A Hajat; M Crawford; F Mostashari
Journal:  MMWR Suppl       Date:  2004-09-24

2.  Forecasting seasonal outbreaks of influenza.

Authors:  Jeffrey Shaman; Alicia Karspeck
Journal:  Proc Natl Acad Sci U S A       Date:  2012-11-26       Impact factor: 11.205

3.  A method for detecting and characterizing outbreaks of infectious disease from clinical reports.

Authors:  Gregory F Cooper; Ricardo Villamarin; Fu-Chiang Rich Tsui; Nicholas Millett; Jeremy U Espino; Michael M Wagner
Journal:  J Biomed Inform       Date:  2014-08-30       Impact factor: 6.317

4.  Absolute humidity and the seasonal onset of influenza in the continental United States.

Authors:  Jeffrey Shaman; Virginia E Pitzer; Cécile Viboud; Bryan T Grenfell; Marc Lipsitch
Journal:  PLoS Biol       Date:  2010-02-23       Impact factor: 8.029

5.  Real-time epidemic monitoring and forecasting of H1N1-2009 using influenza-like illness from general practice and family doctor clinics in Singapore.

Authors:  Jimmy Boon Som Ong; Mark I-Cheng Chen; Alex R Cook; Huey Chyi Lee; Vernon J Lee; Raymond Tzer Pin Lin; Paul Ananth Tambyah; Lee Gan Goh
Journal:  PLoS One       Date:  2010-04-14       Impact factor: 3.240

6.  Forecasting peaks of seasonal influenza epidemics.

Authors:  Elaine Nsoesie; Madhav Mararthe; John Brownstein
Journal:  PLoS Curr       Date:  2013-06-21

7.  Detecting influenza epidemics using search engine query data.

Authors:  Jeremy Ginsberg; Matthew H Mohebbi; Rajan S Patel; Lynnette Brammer; Mark S Smolinski; Larry Brilliant
Journal:  Nature       Date:  2009-02-19       Impact factor: 49.962

8.  Probabilistic, Decision-theoretic Disease Surveillance and Control.

Authors:  Michael Wagner; Fuchiang Tsui; Gregory Cooper; Jeremy U Espino; Hendrik Harkema; John Levander; Ricardo Villamarin; Ronald Voorhees; Nicholas Millett; Christopher Keane; Anind Dey; Manik Razdan; Yang Hu; Ming Tsai; Shawn Brown; Bruce Y Lee; Anthony Gallagher; Margaret Potter
Journal:  Online J Public Health Inform       Date:  2011-12-22

9.  Potential impact of antiviral drug use during influenza pandemic.

Authors:  Raymond Gani; Helen Hughes; Douglas Fleming; Thomas Griffin; Jolyon Medlock; Steve Leach
Journal:  Emerg Infect Dis       Date:  2005-09       Impact factor: 6.883

10.  Probabilistic case detection for disease surveillance using data in electronic medical records.

Authors:  Fuchiang Tsui; Michael Wagner; Gregory Cooper; Jialan Que; Hendrik Harkema; John Dowling; Thomsun Sriburadej; Qi Li; Jeremy U Espino; Ronald Voorhees
Journal:  Online J Public Health Inform       Date:  2011-12-22
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