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Results from the centers for disease control and prevention’s predict the 2013–2014 Influenza Season Challenge

Overview of attention for article published in BMC Infectious Diseases, July 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (97th percentile)

Mentioned by

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2 news outlets
policy
1 policy source
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18 X users
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1 Facebook page

Citations

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159 Dimensions

Readers on

mendeley
125 Mendeley
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1 CiteULike
Title
Results from the centers for disease control and prevention’s predict the 2013–2014 Influenza Season Challenge
Published in
BMC Infectious Diseases, July 2016
DOI 10.1186/s12879-016-1669-x
Pubmed ID
Authors

Matthew Biggerstaff, David Alper, Mark Dredze, Spencer Fox, Isaac Chun-Hai Fung, Kyle S. Hickmann, Bryan Lewis, Roni Rosenfeld, Jeffrey Shaman, Ming-Hsiang Tsou, Paola Velardi, Alessandro Vespignani, Lyn Finelli, for the Influenza Forecasting Contest Working Group

Abstract

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. 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). 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. 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.

X Demographics

X Demographics

The data shown below were collected from the profiles of 18 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 125 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 125 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 23 18%
Student > Master 21 17%
Researcher 17 14%
Other 8 6%
Student > Doctoral Student 6 5%
Other 21 17%
Unknown 29 23%
Readers by discipline Count As %
Computer Science 23 18%
Medicine and Dentistry 19 15%
Agricultural and Biological Sciences 12 10%
Mathematics 11 9%
Social Sciences 6 5%
Other 19 15%
Unknown 35 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 30. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 22 January 2018.
All research outputs
#1,287,842
of 25,193,883 outputs
Outputs from BMC Infectious Diseases
#305
of 8,488 outputs
Outputs of similar age
#24,232
of 373,746 outputs
Outputs of similar age from BMC Infectious Diseases
#5
of 199 outputs
Altmetric has tracked 25,193,883 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,488 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.6. This one has done particularly well, scoring higher than 96% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 373,746 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 93% of its contemporaries.
We're also able to compare this research output to 199 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 97% of its contemporaries.