At a glance
- CFA and NCIRD estimate epidemic trends based on the time-varying reproductive number, Rt, a measure of community disease transmission that helps quickly assess whether infections are increasing or decreasing. This measure helps public health practitioners prepare and respond.
- This page shows epidemic trends at the Health Service Area level where available, offering more localized trends than statewide reports. Use the "View State Map" toggle to view current state-level trends.
COVID-19
As of June 2, 2026, we estimate that COVID-19 infections are growing or likely growing in 1 state, declining or likely declining in 41 states, and not changing in 8 states. Previous estimates can be found on data.cdc.gov.
Epidemic trend is estimated at the national, state, and health service area (HSA) levels for the United States. HSA is a geographic area that combines one or more contiguous counties to form a region that is relatively self-contained with respect to hospital care. The National Center for Health Statistics (NCHS), which is part of Centers for Disease Control and Prevention (CDC), was originally responsible for defining HSAs. The HSA's shown here align with state boundaries. More information on HSAs is available here.
Influenza
As of June 5, 2026, estimates of influenza Rt have ended for the 2025-2026 season and will begin again in the 2026-2027 season. Previous estimates can be found on data.cdc.gov.
RSV
As of June 5, 2026, estimates of RSV Rt have ended for the 2025-2026 season and will begin again in the 2026-2027 season. Previous estimates can be found on data.cdc.gov.
Epidemic trend overview
Epidemic trend categories indicate the probability that the number of infections is currently growing. Epidemic trends indicate direction only and do not reflect the burden of disease, therefore they should be used alongside other surveillance metrics (such as the percentage of ED visits, which are displayed in the callout boxes in the map) for a more complete picture. View a summary of key data for COVID-19, influenza, and RSV.
The epidemic trend category is based on the probability that the estimated time-varying reproductive number (Rt, a measure of community disease transmission) is greater than 1, indicating epidemic growth. See below for details on categorization.
For this webpage, Rt is estimated from daily incident emergency department visits reported through the National Syndromic Surveillance Program. Read more about how to interpret Rt in our Modeling Handbook and how Rt and the epidemic trends presented here are estimated in our Behind the Model.
Detailed Methods
- Rt is a data-driven measure of disease transmission. The value of Rt is the estimated average number of new infections caused by each infectious person at time t. Rt accounts for current population characteristics, population susceptibility, public health interventions, and behavior.
- Rt > 1 indicates that infections are growing because, on average, each infected person is causing more than one new infection, while Rt < 1 indicates that infections are declining.
- Rt can be an early indicator of future increases or decreases in cases, hospitalizations, or deaths, because transmission occurs before case confirmation, hospitalization, or death.
- The distribution and uncertainty range for each Rt estimate determines the probability that infections are growing. For example, if 75% of the distribution falls above 1, then there is a 75% chance that the infections are growing in that location. A wider distribution reflects greater uncertainty in the true epidemic trend at that time.
- Read about interpreting Rt in our Modeling Handbook.
Rt is defined as the average number of new infections caused by each infectious person at a particular time, t. When Rt>1, infections are growing, and when Rt<1, infections are declining. We estimate a distribution of possible Rt values based on observed emergency department visit data and model assumptions, then we assign categories shown in the maps above based on the proportion of the distribution where Rt>1.
- Growing: >90% of the distribution of Rt >1
- Likely Growing: 75%-90% of the distribution of Rt > 1
- Not Changing: 25%-75% of the distribution of Rt > 1 (in this case, the distribution spans across 1, and contains a mix of values above and below 1.)
- Likely Declining: 10%-25% of the distribution of Rt > 1; this is equivalent to 75%-90% of the distribution of Rt ≤ 1
- Declining: <10% of the distribution of Rt > 1; this is equivalent to >90% of the distribution of Rt ≤ 1
- Not Estimated: Rt is not estimated in the following cases: 1) there is insufficient data to calculate a trend (specifically, there were no reported ED visits for the condition of interest on >20% of the dates in the past 8 weeks), 2) there have been recent sustained anomalies detected in reported ED visit values, and/or 3) the model did not pass checks for reliability.
- Data Unavailable: Jurisdiction does not participate in data-sharing at this geographic scale for trend estimation
The data used to estimate Rt are updated frequently, and initial reported counts might later be revised. We manually review the data weekly and occasionally exclude implausible outlier values, but may still estimate Rt.
- Rt estimates are sensitive to assumptions about the length of time between a person becoming infected and spreading the infection to someone else, referred to as the "generation interval." This length of time varies for each infector-infectee pair and is described as a distribution. The generation interval distribution is different for each pathogen and is also influenced by human behavior, social connectedness, and public health interventions.
- Rt estimates may be over- or under-estimated if the proportion of infections that result in emergency department visits changes abruptly. These estimates can be impacted by shifts in clinical severity, increased or decreased use of clinical testing, or changes in reporting.
- Learn more about our method for calculating Rt in our Behind the Model.