What to know
Interpretation of Forecasts of New Hospital Admissions
- Ensemble forecasts combine forecasts from all submitted models into one forecast. These forecasts have been among the most accurate for previous influenza forecasting efforts but may not reliably predict rapid changes in disease trends.
- This week, 29 modeling groups contributed 34 forecasts that were eligible for inclusion in the ensemble forecasts for at least one jurisdiction. Contributing teams are listed below.
- The figure shows the number of new laboratory confirmed influenza hospital admissions reported in the United States each week from November 2024 through March 1, 2025 and forecasted new influenza hospital admissions per week for this week and the next 2 weeks, through March 22, 2025. The colored areas on the graph show prediction intervals, which indicate the bounds of uncertainty around the forecast estimates.
National and State Forecasts
Forecasted weekly hospital admissions
Forecasts for week ending
Forecasted hospital admissions ( per 100,000 people)
prediction interval: – hospital admissions (– per 100,000 people)
( prediction interval) based on forecasts submitted by
See the for:
Forecasts of Weekly Hospital Admissions:
Based on forecasts submitted by
hospital admissions
Forecasted hospital admissions
(% prediction interval: - hospital admissions)
Forecast median | prediction interval | Name |
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Select Models
Click on models to see and compare forecasts
- The forecasted hospital admission rates (for both median and prediction intervals) use population estimates as a population denominator for the state. We note that the denominator for rates may not capture the exact catchment populations of the hospitals in each state, but rates provide a rough adjustment for population size, allowing comparison across states with different population sizes.
- Hospitals are required to report weekly laboratory-confirmed influenza hospitalizations to the . See Guidance for Hospital Reporting and FAQs for additional details on this guidance.
- The following jurisdictions had <80% of hospitals reporting for the most recent week: Alaska, Arkansas, District of Columbia, Georgia, Hawaii, Iowa, Kansas, Louisiana, Michigan, Mississippi, Montana, New Mexico, Nevada, Oklahoma, Oregon, Puerto Rico, Texas, Vermont and Wyoming. Lower reporting rates could impact forecast validity. Percent of hospitals reporting is calculated based on the number of active hospitals reporting complete data to NHSN for a given reporting week.
- Forecast submissions are collected and stored in the , which also contains more detailed information about the forecast data and submission process.
Additional Reports

State-level forecasts show the predicted number of new laboratory confirmed influenza hospital admissions per week for this week and 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.
Additional forecast data and information about are available.
Contributing Teams and Models
(Model: CADPH-FluCAT_Ensemble)
(Model: CMU-TimeSeries)
(Model: CEPH-Rtrend_fluH)
(Model: CU-ensemble)
(Model: fjordhest-ensemble)
(Model: NIH-Flu_ARIMA)
(Model: Gatech-ensemble_point)
(Model: Gatech-ensemble_prob)
(Model: ISU_NiemiLab-GPE)
(Model: JHUAPL-DMD)
(Model: LUcompUncertLab-chimera)
(Model: MDPredict-SIRS)
(Model: Metaculus-cp)
(Model: MIGHTE-Joint)
(Model: MIGHTE-Nsemble)
(Model: NEU_ISI-AdaptiveEnsemble)
(Model: NEU_ISI-FluBcast)
(Model: MOBS-GLEAM_FLUH)
(Model: OHT_JHU-nbxd)
(Model: PSI-PROF)
(Model: PSI-PROF_beta)
(Model: SigSci-TSENS)
(Model: JHU_CSSE-CSSE_Ensemble)
(Model: UGA_CEID-Walk)
(Model: UGA_flucast-Copycat)
(Model: UGA_flucast-INFLAenza)
(Model: UI_CompEpi-EpiGen)
(Model: UMass-flusion)
(Model: UNC_IDD-InfluPaint)
(Model: UGuelphensemble-GRYPHON)
(Model: UM-DeepOutbreak)
(Model: UVAFluX-CESGCN)
(Model: UVAFluX-Ensemble)
(Model: VTSanghani-PRIME)