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Results from the centers for disease control and prevention’s predict the 2013–2014 Influenza Season Challenge
Open accessAbstract
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.
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The Parable of Google Flu: Traps in Big Data Analysis
Lazer, D., Kennedy, R., King, G., & Vespignani, A. (2014) · Science · doi:10.1126/science.1248506 · Cited by 2,523
Self-citationSalathé, M., & Khandelwal, S. (2011) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002199 · Cited by 530
Salathé, M., Bengtsson, L., Bodnar, T. J., Brewer, D. D., Brownstein, J. S., Buckee, C., Campbell, E. M., Cattuto, C., Khandelwal, S., Mabry, P. L., et al. (2012) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002616 · Cited by 500
Self-citationCook, S., Conrad, C., Fowlkes, A. L., & Mohebbi, M. H. (2011) · PLoS ONE · doi:10.1371/journal.pone.0023610 · Cited by 381
Olson, D. R., Konty, K. J., Paladini, M., Viboud, C., & Simonsen, L. (2013) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003256 · Cited by 320
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Statistical physics of vaccination
Wang, Z., Bauch, C. T., Bhattacharyya, S., d'Onofrio, A., Manfredi, P., Perc, M., Perra, N., Salathé, M., & Zhao, D. (2016) · Physics Reports · doi:10.1016/j.physrep.2016.10.006 · Cited by 872
The RAPIDD Ebola forecasting challenge: synthesis and lessons learnt
Viboud, C., Sun, K., Gaffey, R., Ajelli, M., Fumanelli, L., Merler, S., Zhang, Q., Chowell, G., Simonsen, L., & Vespignani, A. (2018) · Epidemics · doi:10.1016/j.epidem.2017.08.002 · Cited by 251
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Metadata
- Authors
- for the Influenza Forecasting Contest Working Group, Biggerstaff, M., Alper, D., Dredze, M., Fox, S., Fung, I. C.-H., Hickmann, K. S., Lewis, B., Rosenfeld, R., Shaman, J., Tsou, M.-H., Velardi, P., Vespignani, A., & Finelli, L.
- Venue
- BMC Infectious Diseases
- Published
- 2016-07-22
- Volume
- 16
- Issue
- 1
- Pages
- 357-357
- ISSN
- 1471-2334 (ISSN-L)
- OpenAlex
- W2486241280
- Cited by
- 170
- References
- 5
- FWCI
- 22.08
- Type
- journal article
- Language
- en
- Open access
- gold
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- for the Influenza Forecasting Contest Working Group, Biggerstaff, M., Alper, D., Dredze, M., Fox, S., Fung, I. C.-H., Hickmann, K. S., Lewis, B., Rosenfeld, R., Shaman, J., Tsou, M.-H., Velardi, P., Vespignani, A., & Finelli, L. (2016). Results from the centers for disease control and prevention’s predict the 2013–2014 Influenza Season Challenge. BMC Infectious Diseases. https://doi.org/10.1186/s12879-016-1669-x
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