HIV

Data sourcing

The CDC's National Center for HIV, Viral Hepatitis, STD, and TB Prevention (NCHHSTP) collects and studies information on the number of people diagnosed with HIV in the United States. This information is gathered from state and local HIV surveillance programs and is used to better understand the impact of HIV across the country.

A note about CDC NCHHSTP AtlasPlus. The CDC's NCHHSTP and other HIV surveillance programs have agreed to limit the data released at the state and county levels in order to protect the privacy of those affected. It takes 12 months for the data to become official, so the numbers reported before this time are not final and should be interpreted with caution. Additionally, some of the data is adjusted to account for missing information on how people became infected with HIV. This means that the data may change as more information becomes available.

2020 Data Disruption Due to COVID-19. The COVID-19 pandemic significantly disrupted data for the year 2020. This impact could lead to distortions in the reported numbers. Please exercise caution when analyzing this year's data.

The data for 2022 and 2023 is still in its initial stages of collection and has not been finalized, making it "preliminary." Single-year figures refer to data that represents just one specific year rather than an average or cumulative total over multiple years. Given the preliminary status of the 2022 and 2023 data, we've used 2021 as our reference year when showcasing data from a single year.

Variable Data Compilation and Analysis

HIV Diagnoses

Refers to confirmed HIV infections via laboratory or clinical evidence within a specific calendar year. Counts are for individuals aged 13 or older diagnosed with HIV during the year. Age is determined by the person's age at the time of infection. All metrics sourced from the CDC for HIV diagnoses are calculated directly from the raw count of those cases.

HIV Prevalence

Represents estimated individuals aged 13 and older living with HIV by the year's end. Accounts for both diagnosed and undiagnosed cases. They were adjusted using the total number of diagnosed cases and subsequent deaths from the CDC’s Atlas database. The Asian category includes cases classified as "Asian/Pacific Islander" using the pre-1997 OMB race/ethnicity system when querying HIV prevalence. HIV prevalence metrics are determined by estimating the total number of individuals who have ever been infected with HIV (diagnosed and undiagnosed cases) and then adjusting for the reported total number of people diagnosed with HIV and subsequently died provided by the CDC’s Atlas database.

HIV Deaths

Counts deaths of persons aged 13 and older with diagnosed HIV or AIDS, irrespective of death cause. Data has a 12-month reporting delay for CDC reporting. Age is determined by the person's age at the time of death. All metrics sourced from the CDC for HIV deaths are calculated directly from the raw count of those cases.

Algorithms

Percent share

To calculate the percent share of HIV diagnoses, prevalence, or deaths, we divide the number of HIV deaths, diagnoses, or prevalence in a specific demographic group by the total number of HIV deaths, diagnoses, or prevalence and multiply the result by 100.

Formula: Percent Share = (Group # cases ÷ Total # cases) × 100

Population percent

The population data is obtained directly from the CDC. To calculate the population percent share, we divide the number of individuals in a specific population by the total number of individuals in the larger population and multiply the result by 100.

Formula: Population Percent = (Group Pop. ÷ Total Pop.) × 100

Rate Per 100,000 People (also referred to as 'Rate Per 100k')

The rate per 100k for HIV diagnoses, prevalence, and deaths is obtained directly from the CDC. Calculating the rate per 100k of HIV deaths, diagnoses, or prevalence involves dividing the number of deaths, diagnoses, or prevalence within a specific population by the total population of that group, multiplying the result by 100,000, and then expressing it as a rate per 100,000 people.

Formula: Rate per 100,000 people = (Group # cases ÷ Group Pop.) × 100,000

A note about HIV Prevention and Care Rates for Transgender People (2019). Please note: The mentioned groups in our reports refer to sex assigned at birth and not gender identity. Rates per 100k: Unfortunately, due to the absence of reliable population data for gender-expansive individuals, we cannot provide rates per 100k. 2019 Case Counts: Our data sources, based on the CDC's guidelines, do provide case counts for HIV outcomes specifically among Transgender People.

Missing data for HIV deaths, diagnoses, and prevalence

• County-level data is suppressed when the population denominator is less than 100, the total case count is between 1–4 cases, or when querying HIV or AIDS deaths.
• To protect personal privacy, prevent revealing information that might identify specific individuals, and ensure the reliability of statistical estimates, small data values may not be available in some circumstances.
• There isn't enough data to accurately calculate subpopulation rates by age, sex, and race/ethnicity for the Census Island Areas (US territories other than Puerto Rico). As a result, the analysis or report will not provide detailed information about these specific groups in those regions.
• The Asian category includes cases previously classified as "Asian/Pacific Islander" under the pre-1997 Office of Management and Budget (OMB) race/ethnicity classification system when querying HIV prevalence.

Defining PrEP Coverage as a Percentage

PrEP coverage is quantified as a percentage. It represents the ratio of people aged 16 and older who were prescribed PrEP in a given year to the estimated number of individuals in the same age group with indications for PrEP during that year.

Significance of Measuring PrEP Coverage

• Identifying Disparities: This measure sheds light on variations in PrEP accessibility and utilization across diverse demographic segments and geographical zones.
• Monitoring Tool: PrEP coverage percentage serves as an instrument to track shifts in PrEP coverage across periods, aiding in the design of targeted strategies to amplify PrEP uptake and curtail HIV incidence in susceptible groups.
• Representation of Reality: Expressing PrEP coverage as a percentage gives an authentic representation of the fraction of the target population that benefits from PrEP.
• Evaluation Tool: The percentage of PrEP coverage is pivotal in assessing the effectiveness of PrEP implementation and uptake initiatives.

The Interrelation Between PrEP Coverage and Usage

Adequate PrEP coverage is a foundational step towards its utilization. If PrEP coverage is insufficient, high-risk individuals might remain unaware or lack access to PrEP. Consequently, lower PrEP coverage can correlate with reduced PrEP usage, especially in communities with limited access.

Algorithms

All metrics sourced from the CDC are calculated based on the number of PrEP prescriptions provided by the CDC’s Atlas database.

Percent share

Calculating the percent share of PrEP prescriptions involves dividing the number of PrEP prescriptions filled by a specific population or demographic group by the total number of PrEP prescriptions filled and multiplying the result by 100.

Formula: Percent Share = (Group # Rx filled ÷ Total # Rx filled) × 100

PrEP-eligible population percent

Calculating the percent share of the PrEP-eligible population involves dividing the number of individuals within a specific population or demographic group eligible for PrEP by the total number of individuals eligible for PrEP and multiplying the result by 100.

Formula: PrEP-Eligible Population Percent = (Group # eligible ÷ Total # eligible) × 100

PrEP coverage

This percentage is obtained directly from the CDC. It involves dividing the number of individuals within a specific population or demographic group using PrEP at a given time by the total number of individuals in the same population or demographic group eligible for PrEP based on their HIV risk and multiplying the result by 100.

Formula: PrEP Coverage = (Group # using ÷ Group # eligible) × 100

Relative Inequity

Calculating the percentage of relative inequity involves subtracting the proportion of all PrEP prescriptions filled by a specific population or group from the proportion of a specific population or group in the PrEP-eligible population. The value is divided by the proportion of a specific population or group in the PrEP-eligible population multiplied by 100 to express it as a percentage.

Formula: Relative Inequity = ((Use Share − Eligible Pop. Share) ÷ Eligible Pop. Share) × 100

Missing and suppressed PrEP data

• The race and ethnicity of individuals prescribed PrEP are only available for less than 40% of all people prescribed PrEP and are limited to four categories: White, Black, Hispanic/Latino, and Other.
• State-level and county-level PrEP data are not available for race and ethnicity.
• PrEP coverage data are suppressed at any level if the number of persons prescribed PrEP is suppressed, the estimated number of persons with indications for PrEP (PrEP-eligible population) is suppressed, or if the number of persons prescribed PrEP is less than 40.

Linkage to Care

Linkage to HIV care, reported as a percentage, refers to the number of persons aged 13 years and older newly diagnosed with HIV, having at least one CD4 or viral load test performed within one month of diagnosis during the specified year and divided by the number of persons aged 13 years and older newly diagnosed with HIV during the specified year.

Linkage to HIV care is a critical step in the HIV care continuum and can improve health outcomes for individuals with HIV. When a person living with HIV is linked to care soon after their diagnosis, they can receive the medical treatment and support they need to manage their HIV, reduce the amount of virus in their body, improve their health, and lower the risk of transmitting HIV to others. Delayed linkage to care can result in poorer health outcomes for individuals living with HIV and can increase the risk of transmitting HIV to others.

Algorithms

All metrics sourced from the CDC are calculated based on the number of cases of HIV diagnosis where individuals have received at least 1 CD4 or viral load test performed less than one month after diagnosis.

Percent share

Calculating the percent share of individuals who received testing or treatment within a month involves dividing the number of people with access to HIV care in a specific population or demographic group by the total number of people with access to HIV care, and multiplying the result by 100.

Formula: Percent Share = (Group # care access ÷ Total # care access) × 100

Diagnosed population percent

Calculating the percent share of the population involves dividing the number of individuals within a specific population or demographic group with HIV diagnoses by the total number of individuals with HIV diagnoses and multiplying the result by 100.

Formula: Diagnosed Population Percent = (Group # HIV cases ÷ Total # HIV cases) × 100

Linkage to Care

This percentage is obtained directly from the CDC. It involves dividing the number of individuals within a specific population or demographic group with access to care at a given time by the total number of individuals living with HIV in the same population or demographic group and multiplying the result by 100.

Formula: Linkage to Care = (Group # care access ÷ Group # living with HIV) × 100

Relative Inequity

Calculating the percentage of relative inequity involves subtracting the proportion of all individuals with access to care by a specific population or group from the proportion of a specific population or group in the diagnosed population. The value is divided by the proportion of a specific population or group in the diagnosed population multiplied by 100 to express it as a percentage.

Formula: Relative Inequity = ((Access Share − HIV Pop. Share) ÷ HIV Pop. Share) × 100

HIV Stigma

HIV stigma, reported as a score, refers to the weighted median score on a 10-item scale ranging from 0 (no stigma) to 100 (high stigma) among the number of persons aged 18 years and older diagnosed with HIV. This measurement captures four dimensions of HIV stigma: personalized stigma experienced during the past 12 months, current concerns about disclosure, negative self-image, and perceived public attitudes towards people living with HIV.

HIV stigma is crucial in understanding and addressing the challenges faced by individuals living with HIV. By examining stigma, we gain insights into the experiences of people with HIV about personalized stigma, concerns about disclosure, self-image, and societal attitudes. This information helps inform strategies and interventions to reduce stigma, promote social support, and improve the well-being of individuals living with HIV.

Algorithm

All metrics related to HIV stigma are calculated based on a national probability sample of individuals diagnosed with HIV, and are sourced directly from the CDC.

Stigma score

Calculating HIV stigma involves determining the weighted median score on a 10-item scale among a national probability sample of people with diagnosed HIV.

Formula: HIV Stigma Score = Weighted Median of Responses on 10-Item Scale

The scores obtained from self-reported data are then analyzed to assess the prevalence and impact of HIV stigma.

• HIV prevalence (Ages 13+): age: Available; race/ethnicity: Available; sex: Available
• New HIV diagnoses (Ages 13+): age: Available; race/ethnicity: Available; sex: Available
• HIV deaths (Ages 13+): age: Available; race/ethnicity: Available; sex: Available
• HIV prevalence for Black women (Black Women, Ages 13+): age: Available; race/ethnicity: Not available; sex: Not available
• New HIV diagnoses for Black women (Black Women, Ages 13+): age: Available; race/ethnicity: Not available; sex: Not available
• HIV deaths for Black women (Black Women, Ages 13+): age: Available; race/ethnicity: Not available; sex: Not available
• Linkage to HIV care (People diagnosed with HIV, Ages 13+): age: Available; race/ethnicity: Available; sex: Available
• PrEP coverage (PrEP-eligible population, Ages 16+): age: Available; race/ethnicity: Available; sex: Available
• HIV stigma (People living with HIV, Ages 18+): age: Available; race/ethnicity: Available; sex: Available

HIV prevalence

Measurement definition: Individuals ages 13+ living with HIV (diagnosed & undiagnosed) in a particular year.

Clinical importance: HIV is a serious and chronic disease that can be fatal if not treated. However, HIV is now a manageable condition thanks to effective antiretroviral therapy. Studying HIV in regard to health equity can help us to understand why certain populations are more likely to be diagnosed with HIV and why they are less likely to receive effective treatment.

New HIV diagnoses

Measurement definition: Individuals ages 13+ diagnosed with HIV in a particular year.

Clinical importance: HIV is a serious and chronic disease that can be fatal if not treated. However, HIV is now a manageable condition thanks to effective antiretroviral therapy. Studying HIV in regard to health equity can help us to understand why certain populations are more likely to be diagnosed with HIV and why they are less likely to receive effective treatment.

HIV deaths

Measurement definition: Individuals ages 13+ who died from HIV or AIDS in a particular year.

Clinical importance: HIV is a serious and chronic disease that can be fatal if not treated. However, HIV is now a manageable condition thanks to effective antiretroviral therapy. Studying HIV in regard to health equity can help us to understand why certain populations are more likely to be diagnosed with HIV and why they are less likely to receive effective treatment.

HIV prevalence for Black women

Measurement definition: Black or African-American (NH) women ages 13+ living with HIV (diagnosed & undiagnosed) in a particular year.

Clinical importance: Black women are disproportionately affected by HIV. In fact, Black women are six times more likely to be diagnosed with HIV than white women. Studying HIV among Black women in regard to health equity can help us to understand why this disparity exists and how to address it.

New HIV diagnoses for Black women

Measurement definition: Black or African-American (NH) women ages 13+ diagnosed with HIV in a particular year.

Clinical importance: Black women are disproportionately affected by HIV. In fact, Black women are six times more likely to be diagnosed with HIV than white women. Studying HIV among Black women in regard to health equity can help us to understand why this disparity exists and how to address it.

HIV deaths for Black women

Measurement definition: Black or African-American (NH) women ages 13+ who died from HIV or AIDS in a particular year.

Clinical importance: Black women are disproportionately affected by HIV. In fact, Black women are six times more likely to be diagnosed with HIV than white women. Studying HIV among Black women in regard to health equity can help us to understand why this disparity exists and how to address it.

Linkage to HIV care

Measurement definition: Individuals ages 13+ with linkage to HIV care in a particular year. The per 100k rate is the number with linkage to HIV care per 100,000 HIV diagnoses in a particular year.

Clinical importance: Access to quality HIV care is essential for ensuring that people living with HIV can live long and healthy lives. However, not everyone with HIV has access to quality care. Studying HIV care in regard to health equity can help us to understand why these disparities exist and how to improve access to quality care for all people living with HIV.

PrEP coverage

Measurement definition: Individuals ages 16+ prescribed PrEP medication in a particular year. The rate percentage is calculated as the percentage of PrEP-eligible individuals who were prescribed PrEP.

Clinical importance: HIV PrEP is a medication that can help to prevent HIV infection. PrEP is highly effective when taken as prescribed. Studying HIV PrEP in regard to health equity can help us to understand why certain populations are more likely to use PrEP and why others are less likely to use it.

HIV stigma

Measurement definition: Self-reported stigma scores ranging from 0 (no stigma) to 100 (high stigma) for HIV-diagnosed individuals ages 18+ in a particular year.

Clinical importance: HIV stigma often intersects with other forms of stigma and discrimination, such as racism, homophobia, and sexism. Studying HIV stigma can shed light on broader issues of social injustice and inequality.

• CDC - HIV Risk and Prevention
• CDC - HIV Surveillance Reports
• CDC - Resource Library
• HIV Care Continuum
• HIV Treatment as Prevention