Literature DB >> 29506911

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

Matthew Biggerstaff1, Michael Johansson2, David Alper3, Logan C Brooks4, Prithwish Chakraborty5, David C Farrow6, Sangwon Hyun7, Sasikiran Kandula8, Craig McGowan9, Naren Ramakrishnan5, Roni Rosenfeld10, Jeffrey Shaman8, Rob Tibshirani11, Ryan J Tibshirani12, Alessandro Vespignani13, Wan Yang8, Qian Zhang13, Carrie Reed9.   

Abstract

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. Published by Elsevier B.V.

Entities:  

Keywords:  Epidemics; Forecasting; Influenza; Modeling; Prediction

Mesh:

Year:  2018        PMID: 29506911      PMCID: PMC6108951          DOI: 10.1016/j.epidem.2018.02.003

Source DB:  PubMed          Journal:  Epidemics        ISSN: 1878-0067            Impact factor:   4.396


  11 in total

1.  Surveillance for influenza during the 2009 influenza A (H1N1) pandemic-United States, April 2009-March 2010.

Authors:  Lynnette Brammer; Lenee Blanton; Scott Epperson; Desiree Mustaquim; Amber Bishop; Krista Kniss; Rosaline Dhara; Mackenzie Nowell; Laurie Kamimoto; Lyn Finelli
Journal:  Clin Infect Dis       Date:  2011-01-01       Impact factor: 9.079

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.  Type- and Subtype-Specific Influenza Forecast.

Authors:  Sasikiran Kandula; Wan Yang; Jeffrey Shaman
Journal:  Am J Epidemiol       Date:  2017-03-01       Impact factor: 4.897

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

Authors:  Jeffrey Shaman; Virginia Pitzer; Cecile Viboud; Marc Lipsitch; Bryan Grenfell
Journal:  PLoS Curr       Date:  2009-12-18

5.  Real-time numerical forecast of global epidemic spreading: case study of 2009 A/H1N1pdm.

Authors:  Michele Tizzoni; Paolo Bajardi; Chiara Poletto; José J Ramasco; Duygu Balcan; Bruno Gonçalves; Nicola Perra; Vittoria Colizza; Alessandro Vespignani
Journal:  BMC Med       Date:  2012-12-13       Impact factor: 8.775

6.  Modeling the critical care demand and antibiotics resources needed during the Fall 2009 wave of influenza A(H1N1) pandemic.

Authors:  Duygu Balcan; Vittoria Colizza; Andrew C Singer; Christos Chouaid; Hao Hu; Bruno Gonçalves; Paolo Bajardi; Chiara Poletto; Jose J Ramasco; Nicola Perra; Michele Tizzoni; Daniela Paolotti; Wouter Van den Broeck; Alainjacques Valleron; Alessandro Vespignani
Journal:  PLoS Curr       Date:  2009-12-07

7.  Influenza activity - United States, 2014-15 season and composition of the 2015-16 influenza vaccine.

Authors:  Grace D Appiah; Lenee Blanton; Tiffany D'Mello; Krista Kniss; Sophie Smith; Desiree Mustaquim; Craig Steffens; Rosaline Dhara; Jessica Cohen; Sandra S Chaves; Joseph Bresee; Teresa Wallis; Xiyan Xu; Anwar Isa Abd Elal; Larisa Gubareva; David E Wentworth; Jacqueline Katz; Daniel Jernigan; Lynnette Brammer
Journal:  MMWR Morb Mortal Wkly Rep       Date:  2015-06-05       Impact factor: 17.586

Review 8.  Influenza forecasting in human populations: a scoping review.

Authors:  Jean-Paul Chretien; Dylan George; Jeffrey Shaman; Rohit A Chitale; F Ellis McKenzie
Journal:  PLoS One       Date:  2014-04-08       Impact factor: 3.240

Review 9.  A systematic review of studies on forecasting the dynamics of influenza outbreaks.

Authors:  Elaine O Nsoesie; John S Brownstein; Naren Ramakrishnan; Madhav V Marathe
Journal:  Influenza Other Respir Viruses       Date:  2013-12-23       Impact factor: 4.380

10.  Results from the centers for disease control and prevention's predict the 2013-2014 Influenza Season Challenge.

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
Journal:  BMC Infect Dis       Date:  2016-07-22       Impact factor: 3.090

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  36 in total

1.  The future of influenza forecasts.

Authors:  Cécile Viboud; Alessandro Vespignani
Journal:  Proc Natl Acad Sci U S A       Date:  2019-02-08       Impact factor: 11.205

2.  A comparative study on predicting influenza outbreaks using different feature spaces: application of influenza-like illness data from Early Warning Alert and Response System in Syria.

Authors:  Ali Darwish; Yasser Rahhal; Assef Jafar
Journal:  BMC Res Notes       Date:  2020-01-16

3.  Adaptively stacking ensembles for influenza forecasting.

Authors:  Thomas McAndrew; Nicholas G Reich
Journal:  Stat Med       Date:  2021-10-14       Impact factor: 2.373

4.  Universal Nonlinear Infection Kernel from Heterogeneous Exposure on Higher-Order Networks.

Authors:  Guillaume St-Onge; Hanlin Sun; Antoine Allard; Laurent Hébert-Dufresne; Ginestra Bianconi
Journal:  Phys Rev Lett       Date:  2021-10-08       Impact factor: 9.185

Review 5.  Social Media- and Internet-Based Disease Surveillance for Public Health.

Authors:  Allison E Aiello; Audrey Renson; Paul N Zivich
Journal:  Annu Rev Public Health       Date:  2020-01-06       Impact factor: 21.981

6.  Initial growth rates of malware epidemics fail to predict their reach.

Authors:  Lev Muchnik; Elad Yom-Tov; Nir Levy; Amir Rubin; Yoram Louzoun
Journal:  Sci Rep       Date:  2021-06-03       Impact factor: 4.379

7.  Predicting dengue outbreaks at neighbourhood level using human mobility in urban areas.

Authors:  Rafael Bomfim; Sen Pei; Jeffrey Shaman; Teresa Yamana; Hernán A Makse; José S Andrade; Antonio S Lima Neto; Vasco Furtado
Journal:  J R Soc Interface       Date:  2020-10-28       Impact factor: 4.293

8.  Active surveillance documents rates of clinical care seeking due to respiratory illness.

Authors:  Marta Galanti; Devon Comito; Chanel Ligon; Benjamin Lane; Nelsa Matienzo; Sadiat Ibrahim; Atinuke Shittu; Eudosie Tagne; Ruthie Birger; Minhaz Ud-Dean; Ioan Filip; Haruka Morita; Raul Rabadan; Simon Anthony; Greg A Freyer; Peter Dayan; Bo Shopsin; Jeffrey Shaman
Journal:  Influenza Other Respir Viruses       Date:  2020-05-16       Impact factor: 4.380

9.  Nonmechanistic forecasts of seasonal influenza with iterative one-week-ahead distributions.

Authors:  Logan C Brooks; David C Farrow; Sangwon Hyun; Ryan J Tibshirani; Roni Rosenfeld
Journal:  PLoS Comput Biol       Date:  2018-06-15       Impact factor: 4.475

10.  Nonannual seasonality of influenza-like illness in a tropical urban setting.

Authors:  Ha Minh Lam; Amy Wesolowski; Nguyen Thanh Hung; Tran Dang Nguyen; Nguyen Thi Duy Nhat; Stacy Todd; Dao Nguyen Vinh; Nguyen Ha Thao Vy; Tran Thi Nhu Thao; Nguyen Thi Le Thanh; Phan Tri Tin; Ngo Ngoc Quang Minh; Juliet E Bryant; Caroline O Buckee; Tran Van Ngoc; Nguyen Van Vinh Chau; Guy E Thwaites; Jeremy Farrar; Dong Thi Hoai Tam; Ha Vinh; Maciej F Boni
Journal:  Influenza Other Respir Viruses       Date:  2018-08-21       Impact factor: 4.380

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