CDC’s Hospital Respiratory Data (HRD) Methodology

How CDC Ensures High-Quality Hospitalization Data

CDC uses the best available data sources for each step of the process: 

Threshold development (historical patterns):

• • COVID-19: National Healthcare Safety Network (NHSN)
  • Influenza: FluSurv-NET
  • RSV: RSV-NET

These systems provide multi-season, well-characterized data to define what “typical” and “elevated” hospitalization levels look like for each virus.

• • Weekly level calculation (current conditions):
    • All three viruses (COVID-19, influenza, RSV) use NHSN hospital admission data.
    • NHSN provides timely, nationwide reporting from U.S. hospitals, allowing CDC to apply the thresholds consistently each week across all states and virus.

Why this approach is used:

• • This approach leverages strong historical surveillance systems (FluSurv-NET, RSV-NET) to establish reliable benchmarks.
  • It uses real-time, national hospital reporting (NHSN) to monitor current conditions.
  • It ensures consistency and comparability across viruses, locations, and time.

Strong reporting coverage 

• • Most U.S. hospitals report data to NHSN each week, providing broad national coverage 
  • CDC monitors reporting completeness and identifies areas where data may be limited 

Careful data selection 

• • CDC uses multiple recent respiratory seasons to ensure thresholds reflect typical patterns 
  • Unusual time periods (such as the 2020–2021 season) are excluded to avoid bias 

Appropriate geographic methods 

• • Data are analyzed at the state or regional level, depending on where data are most complete and reliable 
  • This ensures levels are stable and comparable across locations 

Ongoing quality checks 

• • CDC evaluates trends, reporting timeliness, and consistency across data sources 
  • Methods and thresholds are reviewed regularly as new data become available 

Why is the Hospital Admissions Level important? 

The Hospital Admissions Level helps people and public health professionals understand and respond to respiratory virus activity. 

For individuals and families:

• • Helps you understand current risk of severe illness in your community
  • Can inform decisions about prevention steps, such as vaccination, masking, or seeking care

For public health and healthcare systems:

• • Provides a standard way to monitor severity across states and regions
  • Helps identify increases or unusual patterns in hospitalizations
  • Supports planning and response, including healthcare capacity and resource allocation

For everyone:

• • Makes complex data easier to understand through a clear, consistent scale
  • Allows comparisons across locations, viruses, and time

CDC recommends using Hospital Admissions Levels alongside other data, such as testing, emergency department visits, and wastewater data, to get a complete picture of respiratory virus activity. 

What data should I look at? 

To understand respiratory virus activity in your area, CDC recommends looking at several types of data together. 

Current levels

• • Show how severe hospitalizations are right now.
  • Are based on the most recent weekly data.

Trends over time

• • Show whether hospitalizations are increasing, decreasing, or staying the same.
  • Look at patterns over several weeks, not just one point in time.

Other respiratory data 

Hospital admissions are one part of the picture. You may also want to look at: 

• • Emergency department visits 

• • Testing data 

• • Wastewater data 

These data can help confirm trends and provide additional context. 

Where to find these data 

• • CDC Respiratory Illness Data Channel:Respiratory Illnesses Data Channel

• • State and local health department websites 

How is the Hospital Admissions Level calculated? 

CDC uses a multi-step process to translate hospital data into five levels that are easy to understand. 

Step 1: Calculate weekly hospitalization rates 

CDC calculates the number of new hospital admissions per 100,000 people each week. 

• • For COVID-19, data come from NHSN and are already summarized 

• • For flu and RSV, CDC combines data from surveillance sites and calculates regional and national rates 

This ensures rates are comparable across viruses and locations. 

Step 2: Use historical data to define levels 

CDC analyzes data from multiple past respiratory seasons to understand what is typical for each virus. 

• • COVID-19: NHSN data 

• • Flu: FluSurv-NET data 

• • RSV: RSV-NET data 

CDC excludes unusual time periods (such as the 2020–2021 season) to improve accuracy. 

CDC then uses a data-driven approach to identify natural groupings in the data and define five levels: 

• • Very Low 

• • Low 

• • Moderate 

• • High 

• • Very High 

Step 3: Set thresholds for each level

CDC defines cut points (thresholds) that separate the five levels.

• • Thresholds are based on how hospitalization rates were distributed in past seasons.
  • Each virus has its own threshold because viruses behave differently.
  • Thresholds may vary by geographic level (state or region) to reflect differences in data availability and patterns.

Step 4: Assign weekly levels

Each week:

• • CDC compares current hospitalization rates (from NHSN) to the thresholds.
  • Each state and virus is assigned a level (Very Low to Very High).

These levels are updated weekly and displayed on CDC’s website. 

Why this approach is used 

• • Data-driven: Based on observed patterns in real data 

• • Comparable: Uses a consistent framework across viruses and locations 

• • Easy to understand: Translates complex data into clear categories 

• • Timely: Uses current hospital data to reflect what is happening now