Datasets:
File size: 4,238 Bytes
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pretty_name: FluSight Forecast Hub — flu hospital admission target
license: cc0-1.0
size_categories:
- 1K<n<10K
tags:
- cadence-weekly
- geo-us
- surveillance-respiratory
- pathogen-influenza
- tier-1
- availability-open
schema_version: '0.1'
source_id: flusight-forecast-hub
source_url: https://github.com/cdcepi/FluSight-forecast-hub
manifest_section: §4.1
surveillance_category: respiratory
pathogens:
- influenza
availability: open
availability_notes: null
access_type: github
tier: 1
cadence: weekly
geography_levels:
- national
- subnational-state
geography_countries:
- US
gold_standard_for: []
vintaged_version_of: null
succeeds: null
derived_from:
- nhsn-hrd
value_columns:
- name: value
unit: admissions/week
value_type: incident
description: Confirmed flu hospital admissions for the epiweek (FluSight scoring target)
aggregation: sum
- name: weekly_rate
unit: admissions/week per 100k
value_type: rate
description: Weekly admission rate per 100k population
aggregation: rate
notes:
extra_columns:
- column: location_name
description: State name as published by the hub. `location_id` is FIPS for states / `US` for national.
interpretation_caveats:
- column: value
caveat: 'This is the *target truth* file the hub uses for scoring. It is derived from NHSN HRD
(`derived_from`) and may lag NHSN by one cycle while the hub freezes the truth value.
For the live admissions series use `nhsn-hrd.totalconfflunewadm` directly.
'
general: 'This source represents only the **truth** half of the hub. Model forecasts live in
`model-output/` in the same repo and will become a separate `flusight-forecast-hub-models`
dataset (forecasts are a different shape — one row per (team, model, reference_date,
target, horizon, location, output_type, value) — and need a separate schema treatment).
'
extra:
hub_format_note: Hubverse — see https://hubverse.io/
forecast_models_separate: true
computed:
last_ingested: '2026-04-26T12:48:54Z'
row_count: 11660
time_coverage:
- start: '2022-02-05'
end: '2026-04-18'
geography_unit_count: 53
observed_cadence_days: 7
missing_gaps: []
data_hash: 1364dce3a6023406
---
# FluSight Forecast Hub — flu hospital admission target
This source represents only the **truth** half of the hub. Model forecasts live in
`model-output/` in the same repo and will become a separate `flusight-forecast-hub-models`
dataset (forecasts are a different shape — one row per (team, model, reference_date,
target, horizon, location, output_type, value) — and need a separate schema treatment).
**Source:** <https://github.com/cdcepi/FluSight-forecast-hub>
## Coverage
- **Time:** 2022-02-05 → 2026-04-18
- **Cadence:** `weekly` (observed median spacing: 7 days)
- **Geography levels:** `national`, `subnational-state` — 53 unique location IDs
- **Countries:** US
- **Pathogens:** `influenza`
- **Surveillance category:** `respiratory`
- **Rows:** 11,660
## Columns
| Column | Unit | value_type | Aggregation | Description |
|--------|------|------------|-------------|-------------|
| `value` | admissions/week | `incident` | `sum` | Confirmed flu hospital admissions for the epiweek (FluSight scoring target) |
| `weekly_rate` | admissions/week per 100k | `rate` | `rate` | Weekly admission rate per 100k population |
### Additional data columns
- **`location_name`** — State name as published by the hub. `location_id` is FIPS for states / `US` for national.
## Interpretation caveats
Things that may differ from how other sources define a similar measure. If you're combining this dataset with another, read these first.
- **`value`** — This is the *target truth* file the hub uses for scoring. It is derived from NHSN HRD
(`derived_from`) and may lag NHSN by one cycle while the hub freezes the truth value.
For the live admissions series use `nhsn-hrd.totalconfflunewadm` directly.
## Related datasets in EPI-Eval
- **Derived from:** `nhsn-hrd`
## Access
- **Availability:** `open`
- **Access type:** `github`
- **License:** cc0-1.0
- **Tier:** 1
---
*Schema version `0.1` · Last ingested 2026-04-26T12:48:54Z · `source_id: flusight-forecast-hub` · Manifest section §4.1*
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