| Title: |
Evaluation of FluSight influenza forecasting in the 2021–22 and 2022–23 seasons with a new target laboratory-confirmed influenza hospitalizations |
| Authors: |
Mathis, Sarabeth M.; Webber, Alexander E.; León, Tomás M.; Murray, Erin L.; Sun, Monica; White, Lauren A.; Brooks, Logan C.; Green, Alden; Hu, Addison J.; Rosenfeld, Roni; Shemetov, Dmitry; Tibshirani, Ryan J.; McDonald, Daniel J.; Kandula, Sasikiran; Pei, Sen; Yaari, Rami; Yamana, Teresa K.; Shaman, Jeffrey; Agarwal, Pulak; Balusu, Srikar; Gururajan, Gautham; Kamarthi, Harshavardhan; Prakash, B. Aditya; Raman, Rishi; Zhao, Zhiyuan; Rodríguez, Alexander; Meiyappan, Akilan; Omar, Shalina; Baccam, Prasith; Gurung, Heidi L.; Suchoski, Brad T.; Stage, Steve A.; Ajelli, Marco; Kummer, Allisandra G.; Litvinova, Maria; Ventura, Paulo C.; Wadsworth, Spencer; Niemi, Jarad; Carcelen, Erica; Hill, Alison L.; Loo, Sara L.; McKee, Clifton D.; Sato, Koji; Smith, Claire; Truelove, Shaun; Jung, Sung-mok; Lemaitre, Joseph C.; Lessler, Justin; McAndrew, Thomas; Ye, Wenxuan; Bosse, Nikos; Hlavacek, William S.; Lin, Yen Ting; Mallela, Abhishek; Gibson, Graham C.; Chen, Ye; Lamm, Shelby M.; Lee, Jaechoul; Posner, Richard G.; Perofsky, Amanda C.; Viboud, Cécile; Clemente, Leonardo; Lu, Fred; Meyer, Austin G.; Santillana, Mauricio; Chinazzi, Matteo; Davis, Jessica T.; Mu, Kunpeng; Pastore y Piontti, Ana; Vespignani, Alessandro; Xiong, Xinyue; Ben-Nun, Michal; Riley, Pete; Turtle, James; Hulme-Lowe, Chis; Jessa, Shakeel; Nagraj, V. P.; Turner, Stephen D.; Williams, Desiree; Basu, Avranil; Drake, John M.; Fox, Spencer J.; Suez, Ehsan; Cojocaru, Monica G.; Thommes, Edward W.; Cramer, Estee Y.; Gerding, Aaron; Stark, Ariane; Ray, Evan L.; Reich, Nicholas G.; Shandross, Li; Wattanachit, Nutcha; Wang, Yijin; Zorn, Martha W.; Aawar, Majd Al; Srivastava, Ajitesh; Meyers, Lauren A.; Adiga, Aniruddha; Hurt, Benjamin; Kaur, Gursharn; Lewis, Bryan L.; Marathe, Madhav; Venkatramanan, Srinivasan; Butler, Patrick; Farabow, Andrew; Ramakrishnan, Naren; Muralidhar, Nikhil; Reed, Carrie; Biggerstaff, Matthew; Borchering, Rebecca K. |
| Source: |
Nature Communications, 15(1) |
| Publisher Information: |
Springer Nature |
| Publication Year: |
2024 |
| Collection: |
Carolina Digital Repository (UNC - University of North Carolina) |
| Subject Terms: |
target; horizon; weight; public health response; admission; skills; influenza; influenza epidemics; accurate model; baseline model; weighted interval score; interval scores; response; accurate forecasts; team; model; component models; epidemic; effective public health response; seasonal influenza epidemics; ensemble; hospital; forecast skill; predictors; prediction; period; probabilistic predictions; laboratory-confirmed influenza hospitalizations; influenza hospitalizations; health response |
| Description: |
Accurate forecasts can enable more effective public health responses during seasonal influenza epidemics. For the 2021–22 and 2022–23 influenza seasons, 26 forecasting teams provided national and jurisdiction-specific probabilistic predictions of weekly confirmed influenza hospital admissions for one-to-four weeks ahead. Forecast skill is evaluated using the Weighted Interval Score (WIS), relative WIS, and coverage. Six out of 23 models outperform the baseline model across forecast weeks and locations in 2021–22 and 12 out of 18 models in 2022–23. Averaging across all forecast targets, the FluSight ensemble is the 2nd most accurate model measured by WIS in 2021–22 and the 5th most accurate in the 2022–23 season. Forecast skill and 95% coverage for the FluSight ensemble and most component models degrade over longer forecast horizons. In this work we demonstrate that while the FluSight ensemble was a robust predictor, even ensembles face challenges during periods of rapid change. |
| Document Type: |
article in journal/newspaper |
| Language: |
unknown |
| Relation: |
https://cdr.lib.unc.edu/downloads/pg15bv49s?file=thumbnail; https://cdr.lib.unc.edu/downloads/pg15bv49s |
| DOI: |
10.17615/3sv3-sj27 |
| Availability: |
https://doi.org/10.17615/3sv3-sj27; https://cdr.lib.unc.edu/downloads/pg15bv49s?file=thumbnail; https://cdr.lib.unc.edu/downloads/pg15bv49s |
| Rights: |
http://rightsstatements.org/vocab/InC/1.0/ ; http://creativecommons.org/licenses/by/4.0/ |
| Accession Number: |
edsbas.9DB31EDD |
| Database: |
BASE |