Data for the year 2021 are preliminary. Due to the impact of the COVID-19 pandemic, data for years 2020 and 2021 should be interpreted with caution. Visit coronavirus.gov for the latest Coronavirus Disease (COVID-19) updates.
COVID-19 disruptions in HIV, diagnosis, care and reporting of deaths during 2020 have also made incidence, prevalence, and knowledge of status estimates derived from a CD4-based model, unreliable. Therefore, the HIV surveillance supplemental report Estimated HIV Incidence and Prevalence in the U.S., which provides data on estimated incidence, prevalence, and knowledge of status in the U.S., was not published by CDC this year.

Relative Standard Error (RSE) | AHEAD

Glossary

Learn more about the terminology used in the Ending the HIV Epidemic: A Plan for America initiative.

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Relative Standard Error (RSE)

When the value of an indicator was estimated rather than measured directly, there is always possible error in the estimation based on variation that can occur by chance. This is called a standard error, and it is a measurement of the likely difference between the estimated value and the true value (directly measured value) for the population. Lower percentages are considered more reliable for general use.

The RSE is a measure that shows how large the standard error is, relative to the size of the estimated value. It is calculated by dividing the standard error of an estimated value by the estimated value itself, and then multiplied by 100 and expressed as a percent. Smaller RSEs are indicative of more reliable results, and larger RSEs indicative of less reliable results. On this site, estimates with a relative standard error (RSE) of ≥30% are represented in the following way:

  • Estimates with an RSE of 30%-50% are marked with an asterisk "*", indicating that they should be used with caution.
  • Estimates with an RSE>50% are not shown, and are replaced with the phrase “Data N/A due to high relative standard error.