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Results from the centers for disease control and prevention's predict the 2013-2014 Influenza Season Challenge
Authors
Christopher Allen
David Alper
+74 more
Susan Aman
V. S. Anil Kumar
Anoshã Aslam
Iurii Bakach
Chris Barrett
Stefano BASAGNI
Matthew Biggerstaff
Keith Bisset
David Broniatowski
Logan Brooks
John S. Brownstein
Patrick Butler
Prithwish Chakraborty
Priyadarshini Chandra
Jiangzhuo Chen
Sara Y. Del Valle
Alina Deshpande
Mark Dredze
Rosalind Eggo
Stephen Eubank
Geoffrey Fairchild
David Farrow
Lyn Finelli
Spencer Fox
Isaac Chun Hai Fung
Manoj Gambhir
Nicholas Generous
Francesco GESUALDO
Ed Goldstein
Yi Hao
Jette Henderson
Kyle S. Hickman
Kyle S. Hickmann
James M. Hyman
Sangwon Hyun
Alicia Karspeck
Hemchandra Kaup
Pejman Khadivi
Ramesh Krishnan
Kathy Laskowski
Bryan Lewis
Marc Lipsitch
Kristian Lum
Satish Madhavan
Madhav Marathe
Ashirwad Markar
Sumiko R. Mekaru
Lauren Ancel Meyers
Anna Nagel
Elaine O. Nsoesie
Bryanne Pashley
Michael Paul
NICOLA PERRA
Reid Priedhorsky
Anurekha Ramakrishnan
Naren Ramakrishnan
Roni Rosenfeld
Sam Scarpino
Braydon J. Schaible
James Scott
Jessica K. Sexton
Jeffrey Shaman
Bismark Singh
Ravi Srinivasan
GIOVANNI STILO
Ryan J. Tibshirani
Alberto E. Tozzi
Zion Tsz Ho Tse
Ming Hsiang Tsou
Paola VELARDI
Alessandro Vespignani
Wan Yang
Yuchen Ying
Qian Zhang
Publication date
1 January 2016
Publisher
'Springer Science and Business Media LLC'
Doi
Abstract
Background: Early insights into the timing of the start, peak, and intensity of the influenza season could be useful in planning influenza prevention and control activities. To encourage development and innovation in influenza forecasting, the Centers for Disease Control and Prevention (CDC) organized a challenge to predict the 2013-14 Unites States influenza season. Methods: Challenge contestants were asked to forecast the start, peak, and intensity of the 2013-2014 influenza season at the national level and at any or all Health and Human Services (HHS) region level(s). The challenge ran from December 1, 2013-March 27, 2014; contestants were required to submit 9 biweekly forecasts at the national level to be eligible. The selection of the winner was based on expert evaluation of the methodology used to make the prediction and the accuracy of the prediction as judged against the U.S. Outpatient Influenza-like Illness Surveillance Network (ILINet). Results: Nine teams submitted 13 forecasts for all required milestones. The first forecast was due on December 2, 2013; 3/13 forecasts received correctly predicted the start of the influenza season within one week, 1/13 predicted the peak within 1 week, 3/13 predicted the peak ILINet percentage within 1 %, and 4/13 predicted the season duration within 1 week. For the prediction due on December 19, 2013, the number of forecasts that correctly forecasted the peak week increased to 2/13, the peak percentage to 6/13, and the duration of the season to 6/13. As the season progressed, the forecasts became more stable and were closer to the season milestones. Conclusion: Forecasting has become technically feasible, but further efforts are needed to improve forecast accuracy so that policy makers can reliably use these predictions. CDC and challenge contestants plan to build upon the methods developed during this contest to improve the accuracy of influenza forecasts. © 2016 The Author(s)
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Last time updated on 23/10/2017