Learn more about the data that informs AHEAD.
Uses of these data: Incidence estimates are useful for planning and for the allocation of funds, as well as evaluating the impact of prevention programs.
HIV incidence measures the estimated number of people, whether diagnosed or undiagnosed, newly infected with HIV over a specific period of time, in this case one calendar year. It is important to note that there is a difference between HIV “incidence” and “new diagnoses” of HIV infection. HIV incidence refers to persons newly infected with HIV, whereas individuals newly diagnosed with HIV may have been infected years before actually being diagnosed. For instance, a person may have been HIV+ for a period of time (prior to getting tested and diagnosed) but may have been unaware that they were HIV+ until they tested and received a diagnosis much later. So, the year they are diagnosed may not be the same as the year they actually became HIV+.
Estimates derived by using HIV surveillance data and CD4 data for persons aged ≥13 years at diagnosis. Incidence estimates are useful in many ways, including but not limited to:
Policy and Programmatic Planning Efforts
Making Decisions around Funding Allocations
Evaluating the Impact of Prevention Programs
For example, these estimates can be used to assess changes in characteristics of persons most at risk for acquiring HIV infection.
CD4 Depletion Model
CD4+ T-lymphocyte (CD4) cells are a type of white blood cell that help to fight infection. HIV harms CD4 cells, and without treatment, HIV reduces the total number of CD4 cells in the body over time. Because these cells are key to fighting infection and keeping us healthy, CD4 counts are used to determine the health of an HIV+ person’s immune system, and by extension, stage of the disease. The three stages of HIV infection are (1) acute HIV infection, (2) chronic HIV infection, and (3) acquired immunodeficiency syndrome (AIDS).
HIV incidence was calculated using the result of the first CD4+ T-lymphocyte (CD4) test after initial HIV diagnosis and the CD4 Depletion Model (CD4 model). The first CD4 test results after HIV diagnosis are routinely collected by all jurisdictions as part of the National HIV Surveillance System (NHSS).
The CD4 Model allows for subject-specific estimates of expected time to cross a specific CD4 threshold. The model also is used to estimate the subject-specific probability of having a CD4 count above a pre-specified threshold at specific timepoints.
Before initial treatment, the CD4 cell count can be used to estimate the time from infection to the date of the CD4 test. The CD4 model was applied to NHSS data to estimate (1) the distribution of delay from infection to diagnosis and then to (2) produce incidence and prevalence estimates of HIV among adults and adolescents. Of note, reporting of the first CD4 test result after diagnosis of HIV infection is a required data element on the HIV case report form; however, completeness of reporting varies among states and local jurisdictions. Estimates should be interpreted with caution for EHE areas (including Phase 1 EHE states, EHE jurisdictions, or states that contain EHE jurisdictions) that do not have laws requiring complete reporting of laboratory data or have incomplete reporting. Estimates should be interpreted with caution for jurisdictions that do not have laws requiring complete reporting of laboratory data or have incomplete reporting. Areas without laws: Idaho and New Jersey. Areas with incomplete reporting: Kentucky, Pennsylvania (excluding Philadelphia), Vermont, and Puerto Rico.
HIV incidence among adults and adolescents were obtained via the following:
Among all HIV diagnoses reported by states to the CDC, the date of HIV infection was estimated for each person with a CD4 test by using the CD4 depletion model.
The distribution of delay (from HIV infection to diagnosis) was used to estimate the annual number of HIV incidences, (new infections in a given year) which includes persons with diagnosed infections and persons with undiagnosed infection.
Estimates rounded to the nearest 100 for estimates > 1,000 and to the nearest 10 for estimates ≤ 1,000 to reflect model uncertainty. Relative standard errors (RSEs) were calculated for estimates of incidence, prevalence, and percentages of persons living with diagnosed HIV infection and were used to determine the reliability of estimates. Estimates with a RSE of < 30% meet the standard of reliability and is displayed. Estimates with a RSE of 30%–50% meet a lower standard of reliability and is displayed but should be interpreted with caution. Estimates with a RSE of > 50% are statistically unreliable and not displayed. Estimates with a relative standard error (RSE) of ≥30% do not meet the standard of reliability and 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.”
Estimates should be interpreted with caution for jurisdictions that do not have laws requiring complete reporting of laboratory data or have incomplete reporting. Areas without laws: Idaho and New Jersey. Areas with incomplete reporting: Kentucky, Pennsylvania (excluding Philadelphia), Vermont, and Puerto Rico.
Due to the impact of the COVID-19 pandemic, data for the year 2020 should be interpreted with caution. 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.
For more details, please refer to the following source:
- Centers for Disease Control and Prevention. Terms, Definitions, and Calculations Used in CDC HIV Surveillance Publications. Available at: Terms, Definitions, and Calculations | Surveillance Overview | Statistics Center | HIV/AIDS | CDC (Accessed: May 14, 2021).
More information about HIV Incidence data can be found at: HIV Surveillance Report Supplemental Report Volume 26, Number 1.
The most recent CDC HIV Incidence data can be found at: HIV Surveillance Data Tables 2021, Vol. 2, No. 2.