Forecasts of Flu Hospitalizations February 14, 2023

Updated February 16, 2023

Reported and forecasted new influenza hospitalizations as of February 14, 2023.

Interpretation of National Forecasts of New Hospitalizations

  • This week’s ensemble predicts that the number of new weekly confirmed influenza hospital admissions will remain stable or have an uncertain trend nationally, with 360 to 3,500 new confirmed influenza hospital admissions likely reported in the week ending February 25, 2023.
  • This week, 20 modeling groups contributed 21 forecasts that were eligible for inclusion in the ensemble forecasts for at least one jurisdiction. Contributing teams are listed below.
  • Ensemble forecasts combine forecasts from diverse models into one forecast. They have been among the most reliable forecasts in performance for previous influenza and COVID-19 forecasting efforts, but even the ensemble forecasts may not reliably predict rapid changes.
  • The figure shows the number of new confirmed influenza hospital admissions reported in the United States each week from September 1 through February 11 and forecasted new influenza hospital admissions per week over the next 2 weeks, through February 25. Hospitals are required to report laboratory-confirmed influenza hospitalizations to HHS Protect daily. See COVID-19 Guidance for Hospital Reporting and FAQs [669 KB, 52 pages] for additional details on this guidance.

National Forecast Incident Hospitalizations 2023-02-13

State Forecasts

State-level forecasts show the predicted number of new influenza hospital admissions per week for the next 2 weeks by state. Each state forecast figure uses a different scale due to differences in the number of new influenza hospital admissions per week between states and only forecasts included in the ensemble are shown. Plots of the state-level ensemble forecasts and the underlying data can be downloaded below.

Download state forecasts [PDF – 693 KB]

Download all forecast data [XLS – 203 KB]

Additional forecast data and information about submitting forecasts are available at

Contributing Teams

California Department of Public Health (CADPH) (Model: FluCAT)

Carnegie Mellon Delphi Group (Model: CMU-TimeSeries)

CEPH Lab at Indiana University (Model: Rtrend_fluH)

Columbia University (Model: CU-ensemble)

Fogarty International Center, National Institutes of Health (NIH) (Model: Flu_ARIMA)

Georgia Institute of Technology (Model: GT-FluFNP)

Iowa State Niemi Research Lab (Model: Flu Forecast)

Johns Hopkins ID Dynamics (Model: CovidScenarioPipeline)

Los Alamos National Lab and Northern Arizona University (Model: LosAlamos_NAU-CModel_Flu)

LU Computational Uncertainty Lab (Model: LUcompUncertLab-humanjudgment)

MIGHTE (Model: Nsemble)

MOBS Lab at Northeastern (Model: MOBS-GLEAM_FLUH)

Predictive Science Inc. (Model: PSI-DICE)

Signature Science (Model: SigSci-CREG)

Signature Science (Model: SigSci-TSENS)

Srivastava Group (Model: SGroup-RandomForest)

UGA_flucast (Model: UGA_flucast-OKeeffe)

UNC Infectious Disease Dynamics (Model: InfluPaint)

University of Georgia Center for the Ecology of Infectious Diseases Forecasting Working Group (Model: CEID-Walk)

University of Massachusetts-Amherst (Model: UMass-trends_ensemble)

University of Virginia, Biocomplexity Institute (Model: UVAFluX-Ensemble)