Results from the second year of a collaborative effort to forecast influenza seasons in the United States

被引:67
作者
Biggerstaff, Matthew [1 ]
Johansson, Michael [2 ]
Alper, David [3 ]
Brooks, Logan C. [4 ]
Chakraborty, Prithwish [5 ]
Farrow, David C. [6 ]
Hyun, Sangwon [7 ]
Kandula, Sasikiran [8 ]
McGowan, Craig [1 ]
Ramakrishnan, Naren [5 ]
Rosenfeld, Roni [9 ]
Shaman, Jeffrey [8 ]
Tibshirani, Rob [10 ]
Tibshirani, Ryan J. [11 ]
Vespignani, Alessandro [12 ]
Yang, Wan [8 ]
Zhang, Qian [12 ]
Reed, Carrie [1 ]
机构
[1] Ctr Dis Control & Prevent, Epidemiol & Prevent Branch, Influenza Div, Atlanta, GA USA
[2] Ctr Dis Control & Prevent, Dengue Branch, Div Vector Borne Dis, Atlanta, GA USA
[3] Everyday Hlth, New York, NY USA
[4] Carnegie Mellon Univ, Dept Comp Sci, Pittsburgh, PA USA
[5] Virginia Tech, Discovery Analyt Ctr, Dept Comp Sci, Blacksburg, VA USA
[6] Carnegie Mellon Univ, Dept Computat Biol, Pittsburgh, PA USA
[7] Carnegie Mellon Univ, Deptartment Stat, Pittsburgh, PA USA
[8] Columbia Univ, Dept Environm Hlth Sci, Mailman Sch Publ Hlth, New York, NY USA
[9] Carnegie Mellon Univ, Deptartment Machine Learning, Dept Language Technol, Dept Computat Biol,Dept Comp Sci, Pittsburgh, PA USA
[10] Stanford Univ, Dept Stat, Dept Hlth Res & Policy, Stanford, CA 94305 USA
[11] Carnegie Mellon Univ, Dept Machine Learning, Deptartment Stat, Pittsburgh, PA USA
[12] Northeastern Univ, Boston, MA 02115 USA
关键词
Influenza; Epidemics; Forecasting; Prediction; Modeling; OUTBREAKS;
D O I
10.1016/j.epidem.2018.02.003
中图分类号
R51 [传染病];
学科分类号
100401 ;
摘要
Accurate forecasts could enable more informed public health decisions. Since 2013, CDC has worked with external researchers to improve influenza forecasts by coordinating seasonal challenges for the United States and the 10 Health and Human Service Regions. Forecasted targets for the 2014-15 challenge were the onset week, peak week, and peak intensity of the season and the weekly percent of outpatient visits due to influenza-like illness (ILI) 1-4 weeks in advance. We used a logarithmic scoring rule to score the weekly forecasts, averaged the scores over an evaluation period, and then exponentiated the resulting logarithmic score. Poor forecasts had a score near 0, and perfect forecasts a score of 1. Five teams submitted forecasts from seven different models. At the national level, the team scores for onset week ranged from < 0.01 to 0.41, peak week ranged from 0.08 to 0.49, and peak intensity ranged from < 0.01 to 0.17. The scores for predictions of ILI 1-4 weeks in advance ranged from 0.02-0.38 and was highest 1 week ahead. Forecast skill varied by HHS region. Forecasts can predict epidemic characteristics that inform public health actions. CDC, state and local health officials, and researchers are working together to improve forecasts.
引用
收藏
页码:26 / 33
页数:8
相关论文
共 19 条
[1]  
[Anonymous], PLOS CURR
[2]  
Appiah GD, 2015, MMWR-MORBID MORTAL W, V64, P583
[3]  
Balcan Duygu, 2009, PLoS Curr, V1, pRRN1133
[4]   Results from the centers for disease control and prevention's predict the 2013-2014 Influenza Season Challenge [J].
Biggerstaff, Matthew ;
Alper, David ;
Dredze, Mark ;
Fox, Spencer ;
Fung, Isaac Chun-Hai ;
Hickmann, Kyle S. ;
Lewis, Bryan ;
Rosenfeld, Roni ;
Shaman, Jeffrey ;
Tsou, Ming-Hsiang ;
Velardi, Paola ;
Vespignani, Alessandro ;
Finelli, Lyn .
BMC INFECTIOUS DISEASES, 2016, 16
[5]   Surveillance for Influenza during the 2009 Influenza A (H1N1) Pandemic-United States, April 2009-March 2010 [J].
Brammer, Lynnette ;
Blanton, Lenee ;
Epperson, Scott ;
Mustaquim, Desiree ;
Bishop, Amber ;
Kniss, Krista ;
Dhara, Rosaline ;
Nowell, Mackenzie ;
Kamimoto, Laurie ;
Finelli, Lyn .
CLINICAL INFECTIOUS DISEASES, 2011, 52 :S27-S35
[6]   Flexible Modeling of Epidemics with an Empirical Bayes Framework [J].
Brooks, Logan C. ;
Farrow, David C. ;
Hyun, Sangwon ;
Tibshirani, Ryan J. ;
Rosenfeld, Roni .
PLOS COMPUTATIONAL BIOLOGY, 2015, 11 (08)
[7]  
Centers for Disease Control and Prevention, 2016, FLU ACT FOR WEBS LAU
[8]  
Centers for Disease Control and Prevention, 2013, FED REGISTER, V78, P70303
[9]  
Centers for Disease Control and Prevention, 2014, OV INFL SURV US
[10]  
Centers for Disease Control and Prevention, 2014, FLUV INT