FAQs

Why are the data not from this year?

Each year, AIDSVu publishes the latest HIV data available from CDC and nearly 50 local health departments. The state-, county-, and city-level prevalence and new diagnoses data have about a one-year compilation period to allow for reporting time, data corrections, resolution of duplicate diagnoses across states, analyses, and report preparation. New diagnoses data offer a look at recent changes in the epidemic.

City-level data are available more quickly than the state- and county-level data due to the different data sources and their independent timelines.

Why aren’t some data shown?

To protect the privacy of those living with diagnosed HIV, AIDSVu does not display data where the number of people living with diagnosed HIV is less than five and/or the number of people in the area is less than 100 for states/counties and less than 500 for ZIP Codes/census tracts.

Areas appear white when one or both conditions are met. The darker shade of gray indicates an area where data are not shown because the data are either not available for the area or were not released to AIDSVu.

Why do the maps look different compared to last year?

The state- and county-level HIV surveillance data on AIDSVu are obtained from the CDC. Each state provides their HIV surveillance data to the CDC, and indicates, through a data re-release agreement, if they want their data to be released to the public, and if so, the criteria that must be met in order for the CDC to release their data publicly (i.e., the data suppression threshold). For example, a state may not allow the CDC to release their data to the public if a county within the state (or the whole state at the state-level) has a total population less than a specific threshold (50,000, 500,000, etc.). Data re-release agreements between the states and CDC were updated this year. Several states requested changes in the data suppression thresholds in their data re-release agreements, which is why the maps and the data look different from last year.

What is the difference between data not shown, data not released to AIDSVu, and no cases reported?

The white denotes data not shown to protect privacy because of a small number of cases and/or a small population. This means the number of cases is between 1-4 or the population is less than 100 so the county/state is suppressed to protect the privacy of those individuals.

The lighter grey denotes zero cases reported. This means there were zero people either living with HIV or newly diagnosed with HIV reported to the CDC.

The darker grey denotes data not released to AIDSVu. This means the state has chosen to not allow the CDC to release their data to the public if a county within the state (or the whole state at the state-level) has a total population less than a specific threshold (50,000, 500,000, etc). Each state fills out a data re-release agreement with the CDC where they indicate what level of suppression they would like applied to their state.

These suppression rules apply at both the state and county-level. They also differ depending on the level of stratification. See the data methods for more details.

How does AIDSVu account for prison and jail data and what do the correctional disclaimers on the map mean?

Some counties have state or federal correctional facilities where inmates may have been diagnosed with HIV. Because the data displayed on AIDSVu count these inmates, and because the “persons living with diagnosed HIV” are analyzed by “most recent known address” and “persons newly diagnosed with HIV” data on AIDSVu are analyzed by “residence at HIV diagnosis,” inmates living in or diagnosed at correctional facilities are counted as cases in the county where the facility is located. This may inflate the rate and case count of persons living with an HIV diagnosis in the county and may not represent HIV infection in the county’s community as a whole. In cases where this inflation may occur, a note is included in the pop-up window for the relevant geographic area. See the Data Methods page for additional information about how the inclusion of these correctional notes was determined.

Some AIDSVu cities have excluded case counts where the HIV diagnosis may have occurred in a correctional facility. Correctional disclaimers on AIDSVu’s city maps are on a case-by-case basis. To see cities that display correctional disclaimers, see the Data Methods page.

How are transgender cases defined on AIDSVu?

According to CDC, transgender is defined as people whose gender identity or expression is different from their sex assigned at birth. In 2020, AIDSVu included data provided by 23 city jurisdictions from the electronic HIV/AIDS Reporting System (eHARS) on individuals who are transgender women (Male-to-Female) and/or transgender men (Female-to-Male). The data provided are the estimated number of people living with diagnosed HIV and had a reported difference between birth sex and current gender.

What is the HIV care continuum and why is it important?

The HIV care continuum is a public health model that outlines the stages of care that people living with HIV go through from diagnosis to achieving and maintaining viral suppression – a very low or undetectable amount of HIV in the body. The HIV care continuum is vital in assessing individual care outcomes and population-level progress towards ending the HIV epidemic. Data on the HIV care continuum helps determine if people living with HIV in a given community are engaged in each successive step and where they may be facing barriers and falling out of care. This helps policymakers and service providers better determine where resources and strategies are needed to support people living with HIV to achieve the goal of viral suppression and live long, healthy lives.

What is viral suppression and why is viral suppression important?

Viral suppression is the last step in the HIV care continuum. Viral suppression is when people living with HIV take HIV medication daily as prescribed and reduce the amount of HIV in their blood to a very low, or undetectable, level. People who achieve viral suppression can experience better health outcomes and have effectively no risk of sexually transmitting HIV to their partners. In the U.S., viral suppression is defined as less than 200 copies/mL of HIV in the blood.

Viral suppression is the foundational concept of Undetectable = Untransmittable (U = U) and the “Treatment as Prevention” strategy (TasP), which refers to taking HIV medication to prevent the sexual transmission of HIV. It is a highly effective option for preventing HIV transmission.

At a community level, a high rate of viral suppression indicates a lower chance of HIV transmission among members of the community. A high rate of viral suppression can only be achieved by diagnosing individuals and engaging them in HIV care and treatment.

What HIV care continuum indicators does AIDSVu map?

AIDSVu maps the following steps of the HIV care continuum at the state-level:

• New HIV Diagnoses – Individuals who received a new HIV diagnosis in 2018.
• Late HIV Diagnoses – Individuals diagnosed with stage 3 HIV (AIDS) within 3 months of an initial HIV diagnosis in 2018.
• Linkage to HIV Care – Individuals who visited an HIV health care provider within 1 month of being diagnosed with HIV in 2018.
• Receipt of HIV Care – Individuals living with diagnosed HIV who received medical care for HIV in 2018.
• Viral Suppression – Individuals living with diagnosed HIV who had a low or undetectable viral load (the amount of HIV in the blood) in 2018.

AIDSVu also maps the following steps of the HIV care continuum at the ZIP Code-level:

• New HIV Diagnoses – Individuals who received a new HIV diagnosis between 2014 and 2018.
• Late HIV Diagnoses – Individuals diagnosed with stage 3 HIV (AIDS) within 3 months of an initial HIV diagnoses between 2014 and 2018.
• Linkage to HIV Care – Individuals who visited an HIV health care provider within 1 month of being diagnosed with HIV between 2014-2018.
• Receipt of HIV Care – Individuals living with diagnosed HIV who received medical care for HIV in 2018.
• Viral Suppression – Individuals living with diagnosed HIV who had a low or undetectable viral load (the amount of HIV in the blood) in 2018.

What inspired AIDSVu to add HIV care continuum data and maps?

These data and maps began as a proof of concept with the inaugural Powered By AIDSVu project HIVContinuum.org in February 2015, and now AIDSVu has expanded on this model to include more than 40 states, Washington, DC, and 35 cities at ZIP Code-level across the U.S. The initial project displayed data and maps illustrating the HIV care continuum in eight cities in the U.S. – Atlanta, Chicago, Dallas, New Orleans, New York, Philadelphia, San Francisco, and Washington, D.C. – and two states – Illinois and Texas.

What is the source of AIDSVu’s HIV care continuum data?

State-level HIV care continuum data is obtained from CDC. AIDSVu also collaborates with health departments across the country to display steps of the HIV care continuum, including new diagnoses, late diagnoses, linkage to care, receipt of care, and viral suppression by ZIP Code. To facilitate this, AIDSVu obtained data release agreements directly from the state or local public health departments. As a result, ZIP Code-level data are not directly comparable to the state- and county-level HIV data displayed on AIDSVu, which are obtained from CDC.

For more information about AIDSVu’s data sources and methods, please see the Data Methods.

Why do AIDSVu’s HIV care continuum indicators differ from others like CDC?

AIDSVu emphasizes and continually strives to increase the granularity of its publicly-available data, a perspective that complements CDC’s perspective – which focuses primarily on national, state, and large metropolitan area-level data. As a result, it is not always possible for AIDSVu to follow the same definitions and calculation methods for HIV-related indicators as CDC, but instead follow stricter rules especially for areas below the state level because of issues concerning small numbers (e.g., confidentiality concerns, unstable estimates).

AIDSVu is guided by a decision-making process that includes CDC input, but is separate from CDC. For more information about AIDSVu’s data sources and methods, please see the Data Methods.

Why does AIDSVu map the HIV care continuum?

AIDSVu’s mission is to make HIV-related data widely available, easily accessible, and locally relevant to inform public health decision making. By visualizing data across the HIV care continuum on AIDSVu, health departments, policymakers, researchers, and community leaders are better able to identify disparities in outcomes, develop programs, and allocate resources to improve each step of the care continuum and achieve the goal of viral suppression in their communities.

As community leaders continue to use the HIV care continuum to measure progress toward HIV goals, pinpointing where gaps in services exist is vital. Visualizing where drop-offs are most pronounced, and for what populations, helps decision-makers implement system-wide improvements to support all people living with HIV to successfully navigate the continuum and achieve viral suppression.

What Ending the HIV Epidemic: A Plan for America initiative goals are linked to HIV care continuum indicators?

Progress towards the Ending the HIV Epidemic: A Plan for America (EHE) initiative goals are measured by tracking six indicators. Each indicator reflects public health goals and aligns with the four key strategies of the EHE initiative: diagnose, prevent, treat, and respond. The six EHE indicators are incidence, new diagnoses, knowledge of status, viral suppression, and PrEP use. These indicators represent important steps on the HIV care continuum. For more information on the EHE initiative, visit AIDSVu’s Deeper Look page.

How else can the HIV care continuum data on AIDSVu be utilized, and what continuum resources does AIDSVu have?

State- and ZIP Code-level HIV care continuum maps on AIDSVu can be viewed alongside social determinants of health. Additionally, AIDSVu provides downloadable datasets that researchers, health departments and others can utilize in their own analyses. Check the AIDSVu blog for recent examples data utilization.

AIDSVu also provides aggregated, national-, state-, county- and city-level HIV care continuum data on the local data profiles, including new diagnoses, late diagnoses, linkage to care, receipt of care, and viral suppression with data stratified by age, sex, and race/ethnicity. These data can be viewed with other HIV data to help contextualize the HIV care continuum.

In addition to the data and maps, AIDSVu also features a Deeper Look: Viral Suppression page, which is dedicated to highlighting the importance of the final HIV care continuum step. The page features insights from the data, infographics, and blogs by HIV experts and is updated on an ongoing basis.

Why are HIV care continuum data not available for all AIDSVu cities?

AIDSVu continually strives to increase the granularity of its publicly-available data to support more-informed local public health decision making. To that end, AIDSVu released HIV care continuum data for the cities that were available and able to provide data at this time. AIDSVu will continue to work with additional cities in the coming months to bring more ZIP Code-level continuum data and maps to the site, further empowering communities to understand and visualize their local HIV epidemic.

You can sign up to receive email notifications when new features or data are added to the site.

What is Pre-Exposure Prophylaxis (PrEP)?

Pre-exposure prophylaxis (PrEP) is when people at risk for HIV take HIV medicine daily to lower their chances of getting infected with HIV. When taken every day, PrEP medication can provide a high level of protection against HIV. It can be used as part of a comprehensive prevention strategy, including condoms and other prevention methods, to reduce the risk of sexually transmitted infections (STIs). When someone is exposed to HIV, PrEP can help prevent the virus from establishing a permanent infection in the body. The U.S. Food and Drug Administration (FDA) approved the HIV medicine tenofovir disoproxil fumarate [TDF] in combination with emtricitabine [FTC] (TDF/FTC) for daily use as PrEP in 2012, as well as tenofovir alafenamide [TAF] in combination with emtricitabine [FTC] (TAF/FTC) for daily use as PrEP in 2019. Visit CDC’s “PrEP” page to learn more. AIDSVu currently displays PrEP utilization data through 2018 and therefore does not include any prescriptions of TAF/FTC for PrEP. Please see “Does AIDSVu’s PrEP data include prescriptions of tenofovir alafenamide [TAF] in combination with emtricitabine [FTC] (TAF/FTC)?” below for additional information.

What data do the AIDSVu PrEP maps visualize?

The PrEP data on AIDSVu represent a reliable and consistent estimate of the number of people who had at least one day of prescribed TDF/FTC for PrEP in a calendar year from 2012 to 2018. These individuals are referred to as “PrEP users.” AIDSVu’s PrEP data are calculated to represent the estimated number of PrEP users in each county and state in the U.S. by year. The data represent an underestimate of total PrEP users in a given jurisdiction; the actual number of PrEP users is likely higher. Please see “What are the limitations of the PrEP data?” below for additional information.

The PrEP data on AIDSVu are presented at the county- and state-level and can be viewed as number of PrEP users and rate of PrEP use, expressed as the number of PrEP users per 100,000 people in the population. The data can be broken down by age (year of birth, displayed as 24 and under, 25 to 34, 35 to 44, 45 to 54, 55+) and sex (sex at birth, displayed as male or female). Data on PrEP use can also be viewed alongside social determinants of health at the county- and state-level, such as poverty, high school education, median household income, income inequality, and people without health insurance.

Please see the Data Methods page for additional information.

What is the source of the PrEP data?

The release of PrEP data on AIDSVu was made possible through a unique data-sharing agreement that allowed these proprietary data to be shared publicly for the first time. These data were obtained from Symphony Health with the support of Gilead Sciences, Inc., and compiled by researchers at the Rollins School of Public Health at Emory University.

Symphony Health provided Gilead with national, electronic, patient-level prescription data for TDF/FTC from an overall sample that represents more than 54,000 pharmacies, 1,500 hospitals, 800 outpatient facilities, and 80,000 physician practices across the U.S. This is an open sample of commercially available data, which excludes entities that do not make their data available to Symphony Health, such as closed healthcare systems. The dataset contains prescription, medical, and hospital claims data for all payment types, including commercial plans, Medicare Part D, cash, assistance programs, 340B covered entities, and Medicaid.

All patient-level prescription data were de-identified and linked to confirmatory data from a de-identified medical insurance claims database. A validated algorithm was utilized to exclude TDF/FTC prescriptions that were made for other known indications—such as HIV treatment, post-exposure prophylaxis, and chronic hepatitis B management—or that did not have sufficient medical procedure or diagnosis codes to confirm that the prescription was for PrEP and not for any other use (i.e., “unclassified prescriptions”).

Please see the Data Methods page for additional information.

*MacCannell T, Verma S, Shvachko V, Rawlings K, Mera R. Validation of a Truvada for PrEP Algorithm using an Electronic Medical Record. 8th IAS Conference on HIV Pathogenesis, Treatment & Prevention. Vancouver Canada July 2015.

Who is Symphony Health?

Symphony Health is a leading provider of high-value data, analytics, technology solutions, and actionable insights for healthcare and life sciences manufacturers, payers, and providers. For more information, visit www.symphonyhealth.com.

How was the number of PrEP users by county and state calculated?

The proprietary data collected by Symphony Health were provided to researchers at the Rollins School of Public Health at Emory University and are available at two geographic levels: state and ZIP3. A ZIP3 unit comprises all ZIP codes that share the same first three digits as assigned by the U.S. Postal Service.

Counties may provide a more relevant geographic unit of analysis for PrEP use than ZIP3’s because

counties are governmental divisions that, in most states, hold primary responsibility for public health activities within the counties. For that reason, researchers from Emory applied a validated allocation algorithm using the 2010 U.S. Census ZIP Code Tabulation Area (ZCTA5) to County Relationship file, known as “Crosswalk.” PrEP users residing in ZIP3’s were distributed into overlapping counties according to population weights to obtain the number of PrEP users at the county-level.

The estimates of PrEP users by county and state were then adjusted with state-specific weights of unclassified TDF/FTC prescriptions. This was done to correct for the underestimation of PrEP use due to TDF/FTC prescriptions that could not be linked to medical records to confirm that the prescription was for PrEP and not for any other use.

Although the exact number of PrEP users is unknown, this calculation method accounts for a known source of missing data and provides a reliable and consistent metric for PrEP users at the county- and state-level. The method was adopted from Sullivan et al.’s published article in Annals of Epidemiology titled “Methods for county-level estimation of pre-exposure prophylaxis coverage and application to the U.S. ending the HIV epidemic jurisdictions.”

Finally, data suppression rules were applied to protect persons using PrEP from any potential disclosure of identity by geographic and personal characteristics.

Please see the Data Methods page for additional information.

What types of PrEP data are available on AIDSVu?

AIDSVu has three different PrEP use datasets available on the site, either as interactive maps and/or downloadable datasets. Each dataset is derived using the different calculation methods described below.

1. Raw PrEP Data: These data are proprietary data collected by Symphony Health and then compiled by researchers at the Rollins School of Public Health at Emory University. These data represent a consistent, conservative, and minimum number of PrEP users by county in the U.S. by year. The raw PrEP data are not used for the interactive maps because they are known to substantially underestimate the actual number of PrEP users. However, the raw PrEP data are available as county-level downloadable datasets here.
2. Adjusted PrEP Data (Mapped on AIDSVu): These data are calculated using the raw PrEP data collected by Symphony Health and compiled by Emory University researchers, and then adjusted with state-specific weights of unclassified TDF/FTC prescriptions to estimate the number of PrEP users in each county and state in the U.S. by year. Although the exact number of PrEP users is unknown, this data method accounts for TDF/FTC prescriptions in the Symphony Health dataset that could not be linked to medical records to confirm that the prescription was for PrEP and not for any other use. In other words, this calculation method accounts for missing clinical data and provides a reliable and consistent metric for PrEP users at the county- and state-level. The method was adopted from Sullivan et al.’s published article in Annals of Epidemiology titled “Methods for county-level estimation of pre-exposure prophylaxis coverage and application to the U.S. ending the HIV epidemic jurisdictions.” These data are used to create the interactive county- and state-level PrEP maps and PrEP sections of the local data profiles, and are also available as downloadable datasets for county-, state-, regional-, and national-level here. These data are mapped because they are the most reliable and consistent across the U.S.
3. Best Estimate PrEP Data: These data are derived by upweighting AIDSVu’s adjusted PrEP data to account for the national estimate that 20% of all PrEP medication prescriptions are filled at pharmacies that are not captured in the Symphony Health database. In other words, this calculation method accounts for missing pharmacy data and provides a best estimate of total PrEP users in each county in the U.S. by year. The best estimate PrEP data are not used for AIDSVu’s interactive maps because state-specific estimates of missing pharmacy data are not available. Therefore, the national weight used to derive the best estimates does not represent the full variation in missing TDF/FTC prescriptions at the state-level. However, the best estimate PrEP data are available as county-level downloadable datasets here.

What are the limitations of the PrEP data?

The U.S. healthcare system is very fragmented, and that fragmentation carries over to the way that data is collected and shared across the system. There are a large number of public and private healthcare data collection systems in the U.S.; however, data do not flow among these entities in a cohesive or standardized way. Due to this fact, there is currently no single entity or data source that collects data on all users of PrEP across the U.S. As a result, the exact number of PrEP users is unknown.

The PrEP data on AIDSVu represent a reliable and consistent estimate of the number of PrEP users at the county- and state-level in the U.S. by year. The actual number of PrEP users is likely higher. There are two key reasons for this:

1. AIDSVu’s PrEP dataset is derived from a single data source: Symphony Health. Symphony Health collects data from over 54,000 pharmacies, 1,500 hospitals, 800 outpatient facilities, and 80,000 physician practices across the U.S. However, the dataset does not contain all sources of TDF/FTC prescriptions in the U.S. For example, closed healthcare systems do not share their data with Symphony Health. Additionally, other entities may choose not to share their data with Symphony Health for their own reasons. It is estimated that 20% of all PrEP medication prescriptions nationally are filled at pharmacies that are not captured in the Symphony Health database.
2. AIDSVu’s original PrEP data source also excludes TDF/FTC prescriptions that do not have sufficient medical procedure or diagnosis codes to confirm that the prescription was for PrEP and not for any other use, such as HIV treatment, chronic Hepatitis B treatment, or post-exposure prophylaxis – referred to here as “unclassified prescriptions.” However, only a small minority (6%) of these unclassified prescriptions can be assumed to have been prescribed for purposes other than PrEP. To correct for the underestimation of PrEP use due to unclassified prescriptions, the raw data has been adjusted with state-specific weights of unclassified TDF/FTC prescriptions. This calculation method provides a reliable and consistent metric for PrEP users at the county- and state-level.

Sensitivity analyses of AIDSVu’s 2018 PrEP data were published in both Sullivan et al.’s paper titled “Methods for county-level estimation of pre-exposure prophylaxis coverage and application to the U.S. ending the HIV epidemic jurisdictions” and Siegler et al.’s paper titled “Policy and County-Level Associations with HIV Preexposure Prophylaxis Use, United States, 2018”. A sensitivity analysis is a useful attempt to better understand the extent of missingness in the AIDSVu PrEP dataset. In both papers, the researchers conducted sensitivity analyses on the number of PrEP users in 2018 at the national, state, and EHE jurisdiction-level. The researchers varied plausible values for the proportion of TDF/FTC prescriptions that are not captured in the Symphony Health database. A “best estimate” of the number of PrEP users was chosen based on a previous validation result estimating the percentage of TDF/FTC prescriptions missing from the database to be 20%. In 2018, the AIDSVu dataset included a total of 188,546 PrEP users nationally. A sensitivity analysis that sought to account for missing data identified a national best estimate of all PrEP users to be 235,683, with range of 188,546 to 269,351. Please refer to both papers for more detailed information on the state and county-level results of the sensitivity analyses.

Another known limitation of the PrEP data on AIDSVu is that the county-level data are derived from prescription data collected at the ZIP3 level. A ZIP3 unit comprises all ZIP codes that share the same first three digits as assigned by the U.S. Postal Service. Counties are a more relevant geographic unit of analysis for PrEP use than ZIP3’s because counties are governmental divisions that, in most states, hold primary responsibility for public health activities. For that reason, researchers from Emory applied a validated allocation algorithm using the 2010 U.S. Census ZIP Code Tabulation Area (ZCTA5) to County Relationship file, known as “Crosswalk.” PrEP users residing in ZIP3’s were distributed into overlapping counties according to population weights to obtain an estimate of the number of PrEP users at the county-level. The actual number of PrEP users at the county-level is not known.

What do the PrEP data reveal?

The number of PrEP users increased by 39% from 2017 to 2018, continuing a trend of consistent growth in PrEP use since 2012.

State-level Insights

• States with either Medicaid expansion or a Pre-Exposure Prophylaxis Drug Assistance Program (PrEP-DAP) had a 25% higher rate of PrEP use in 2018 and states with both Medicaid expansion and a PrEP-DAP had a 99% higher rate of PrEP use relative to states in the U.S. without Medicaid expansion or a PrEP-DAP.
  • In 2018, states with a PrEP-DAP had nearly double the rate of PrEP use (100.6 PrEP users per 100,000 population) and double the PrEP-to-Need Ratio (6.4) relative to states without such programs (51.9 PrEP users per 100,000 population and 3.9 PnR).
    • The PrEP-to-Need Ratio (PnR) is the ratio of the number of PrEP users in 2018 to the number of people newly diagnosed with HIV in 2017. It serves as a measurement of how PrEP use compares to the need for PrEP in a population. For example, a PnR of 3.9 means there were 3.9 PrEP users for every person newly diagnosed with HIV in the population.
  • Similarly, U.S. states in 2018 that expanded Medicaid had a PnR that was more than two times higher (6.6) than states that did not expand Medicaid (3.1), indicating fewer PrEP users relative to the need for PrEP in non-Medicaid expansion states.
• Among U.S. Census regions, the Northeast had the highest rate of PrEP use (106.3 PrEP users per 100,000 population) and the highest PnR (8.5) in 2018. That same year, the South had the lowest PnR (3.0) despite having a similar rate of PrEP use (58.6 PrEP users per 100,000 population) to the Midwest (56.8 PrEP users per 100,000 population), indicating fewer PrEP users in the South relative to the need for PrEP in that geographic region.
• PnR for men (5.7) was 3.5 times higher than for women (1.6) in 2018, indicating fewer PrEP users among women relative to their need for PrEP.
  • Out of all PrEP users in 2018, 94% were men and only 6% were women. In comparison, women represented 19% of all new HIV diagnoses in 2018.
• In 2018, the rate of PrEP use and PnR were lowest in those under age 25 (51.5 PrEP users per 100,000 population and 3.3 PnR) and over age 54 (15.9 PrEP users per 100,000 population and 3.7 PnR).
  • People 24 and younger accounted for only 14% of PrEP users in 2018, while representing 21%* of new HIV diagnoses.
  • The PnR for those 24 and younger was lowest (3.3), while the PnR for those 35-44 was almost twice as high (6.1) in 2018, indicating fewer PrEP users relative to the need for PrEP among those 24 and younger.
  • Note: FDA approval for PrEP in adolescents did not occur until mid-2018, which may contribute to relatively low PrEP use in those under 18 years of age.

*Data are preliminary data obtained from CDC ATLAS https://www.cdc.gov/nchhstp/atlas/index.htm.

County-level Insights

• S. counties with the highest proportion of Black residents in 2018 had a higher rate of PrEP use (87.8 PrEP users per 100,000 population) but lower overall PnR (3.4) relative to counties with the lowest proportion of Black residents (41.1 PrEP users per 100,000 population and 7.6).
  • In other words, U.S. counties with the lowest number of Black residents had an overall PnR that was over two times higher (7.6) when compared to counties with the highest number of Black residents (3.4). The lower PnR among counties with the highest proportion of Black residents indicates fewer PrEP users relative to the need for PrEP. Therefore, in 2018 there were 3.4 PrEP users for every person newly diagnosed with HIV in these counties, compared to 7.6 PrEP users for every new HIV diagnosis in counties with the lowest proportion of Black residents.
  • Among U.S. counties, each 5% increase in the proportion of Black residents was associated with a 5% lower overall PnR.
• S. counties with the highest proportion of Latinx residents in 2018 had a higher rate of PrEP use (90.8 PrEP users per 100,000 population) but moderately lower overall PnR (4.5) relative to counties with the lowest proportion of Latinx residents (40.5 PrEP users per 100,000 population and 4.7). The moderately lower PnR among counties with the highest proportion of Latinx residents indicates fewer PrEP users relative to the need for PrEP.
• In 2018, there was a 5% decrease in PnR in counties for each 5% increase in levels of uninsured residents or poverty, indicating lower PrEP use than need for PrEP in counties more impacted by poverty or lack of health insurance. Conversely, there was a 5% increase in PnR for counties with higher proportions of residents with a bachelor’s degree.

Ending the HIV Epidemic: A Plan for America Insights

Among PrEP users in the U.S. in 2018, almost half (49%) were living in the 48 counties targeted by phase one of the Ending the HIV Epidemic: A Plan for America (EHE) Initiative.

• In 2018, 39% of PrEP users in the 48 EHE counties were 25- to 34-years old.
• In 2018, 94% of PrEP users in the 48 EHE counties were men and 6% were women.
• Significant disparities in rates of PrEP use exist across the 48 counties. For example, in San Bernardino County, CA, the rate of PrEP use was 35 PrEP users per 100,000 population in 2018 while there were 644 PrEP users per 100,000 population in San Francisco County, CA.
• The average rate of PrEP use among all EHE counties and cities was 134 PrEP users per 100,000 population.
• By 2018, 24 of the 48 counties, Washington, DC, and San Juan, PR already achieved the National HIV/AIDS Strategy (NHAS) goal to increase PrEP use by 500% from 2015 to 2020. If current PrEP use rates continue, 94% of EHE counties will achieve the NHAS goal by the end of 2020.

Why were these data released on AIDSVu, and why does data on PrEP use matter?

It is said that things that are not measured do not change. AIDSVu’s mission is to make HIV-related data widely available, easily accessible, and locally relevant to inform public health decision making.

Increasing the use of PrEP is a core component of Getting to Zero campaigns in cities and states across the U.S. and is one of four key focus areas in the national initiative, Ending the HIV Epidemic: A Plan for America. AIDSVu’s county- and state-level PrEP data help health departments, elected officials, medical professionals, and community leaders better understand and visualize trends in PrEP use over time, so they can develop programs and policies to increase PrEP awareness and access where it is needed most.

In 2018, AIDSVu released the first-ever state-level data and interactive maps of PrEP users across the U.S. In 2020, AIDSVu released the first-ever county-level data and interactive maps of PrEP users nationwide. By continuing to add new PrEP data, AIDSVu continues its commitment to provide public health officials, policymakers, healthcare professionals, researchers, and community leaders with a more comprehensive view of the HIV epidemic at the local, state, and national levels.

What can the PrEP data on AIDSVu be used for?

The PrEP datasets on AIDSVu provide reliable, consistent, comparable, and replicable numbers of annual PrEP users by county and state. Each calculation method has known limitations that are described in the FAQs and Data Methods. These data are well suited for public health research and planning purposes. For example, these data can be used to:

• Monitor progress, trends, and disparities in PrEP use at the county- and state-level and among specific age groups or sexes;
• Compare relative levels of PrEP use among counties, states, and regions;
• Support research to investigate questions related to PrEP awareness, access, and use; and
• Inform public health planning.

How else can the PrEP data be utilized on AIDSVu, and what other PrEP-related resources does AIDSVu have?

County- and state-level PrEP data on AIDSVu can be viewed alongside social determinants of health and other HIV data, such as new diagnoses, prevalence, and mortality. Additionally, AIDSVu provides downloadable PrEP datasets at the county-, state-, regional- and national-level for researchers and health departments to utilize in their own analyses. Check the AIDSVu blog for recent examples of PrEP data utilization.

In addition to the PrEP data and maps, AIDSVu also features a Deeper Look: PrEP page, which is dedicated to promoting public awareness about PrEP, visualizing key facts about PrEP, and advancing education around PrEP. The page features insights from the data, infographics, and blogs by HIV experts and is updated on an ongoing basis.

AIDSVu also features a PrEP Locator, a national directory of public and private practice providers of PrEP across the U.S. AIDSVu users can find local PrEP providers near them with this valuable tool. The PrEP Locator project was originally developed by Emory University’s Rollins School of Public Health with support from M•A•C AIDS Fund. The PrEP Locator is now managed by CDC’s National Prevention Information Network (NPIN). PrEP provider locations can be overlaid on top of AIDSVu’s PrEP use maps.

How has AIDSVu’s PrEP data evolved?

AIDSVu continually strives to increase the granularity and usefulness of its publicly-available data to inform local public health decision making. Over time, new data methods and data sources for PrEP have surfaced and AIDSVu has improved its PrEP data as a result.

Prior to 2020, AIDSVu mapped raw PrEP data. These data were proprietary data collected by Symphony Health and then compiled by researchers at the Rollins School of Public Health at Emory University. They represented a consistent, conservative, and minimum number of PrEP users by county and state in the U.S. by year and are still available for download at the county-level here.

AIDSVu now has three different PrEP use datasets available on the site, either as interactive maps and/or downloadable datasets. Please see “What types of PrEP data are available on AIDSVu?” above for additional information.

Why do the PrEP data not include race/ethnicity?

There are important challenges associated with race/ethnicity data pertaining to PrEP use, including concerns around privacy, as well as the fact that a large proportion of medical claims data are missing race/ethnicity information. AIDSVu recognizes the significance of better understanding and highlighting trends in racial/ethnic disparities in PrEP use while also ensuring that the data presented are accurate and not biased. To this end, AIDSVu is actively working to publicly release PrEP use data by race/ethnicity at the state-level from Symphony Health in 2020.

In October 2018, CDC published an MMWR article on people prescribed PrEP medication in the U.S. from 2014 to 2016 and their demographic characteristics, including race/ethnicity. The researchers analyzed data from the IQVIA database—a different data source than that presented on AIDSVu—which represents approximately 92% of all prescriptions dispensed from retail pharmacies and 60%–86% dispensed from mail order outlets in the United States. Only 42% of PrEP users identified in the IQVIA database had race/ethnicity information available. The researchers found that among PrEP users with available race/ethnicity data: 68.7% were White, 11.2% were Black, 13.1% were Hispanic, and 4.5% were Asian. When stratified by sex, among female PrEP users with available race/ethnicity data: 48.3% were White, 25.9% were Black, and 17.5% were Hispanic.

Does AIDSVu’s PrEP data include prescriptions of tenofovir alafenamide [TAF] in combination with emtricitabine [FTC] (TAF/FTC)?

AIDSVu currently displays PrEP data through 2018. The FDA approved tenofovir alafenamide [TAF] in combination with emtricitabine [FTC] (TAF/FTC) for PrEP use in October 2019; therefore, the current PrEP use data on AIDSVu does not include any prescriptions of TAF/FTC for PrEP. Future PrEP data updates on AIDSVu will include prescriptions of TAF/FTC for PrEP.

You can sign up on the AIDSVu website to receive email notifications when new features or data are added to the site.

Does AIDSVu’s PrEP data include donations of PrEP medications made by Gilead Sciences to the Ready, Set, PrEP program as part of the Ending the HIV Epidemic: A Plan for America initiative?

AIDSVu currently displays PrEP data through 2018. The Ready, Set, PrEP program was launched in December 2019; therefore, the current PrEP use data on AIDSVu does not include any PrEP medication prescriptions provided through the Ready, Set, PrEP program. Future PrEP data updates on AIDSVu will include PrEP medication prescriptions provided through the Ready, Set, PrEP program. For more information about Ready, Set, PrEP, visit www.getyourprep.com.

You can sign up on the AIDSVu website to receive email notifications when new features or data are added to the site.

How are these data different from other data on PrEP that have been shared publicly?

AIDSVu’s PrEP data are not intended to be compared to any other publicly available data on PrEP use due to the significant differences in data sources and methodologies. Data displayed on AIDSVu represent the estimated number of unique persons, by county and state, who had at least one day in a calendar year of prescribed TDF/FTC for PrEP. On AIDSVu, these individuals are referred to as “PrEP users.”

The PrEP data on AIDSVu represent a reliable and consistent estimate of the number of PrEP users at the county- and state-level in the U.S. by year. The data are subject to the limitations of the dataset as described above and on the Data Methods page.

There is currently no single data source that includes data on all unique users of PrEP across the U.S. Other publicly shared data on PrEP use have derived estimates from different data sources or from multiple data sources. Additionally, data has also been shared publicly on the cumulative number of unique persons who have initiated TDF/FTC for PrEP since 2012, also referred to as “PrEP starts.”

How often will new PrEP data be released?

AIDSVu continually strives to increase the granularity of its publicly-available data to support more-informed local public health decision making. To that end, AIDSVu plans to release updated PrEP maps and data on an annual basis.

You can sign up to receive email notifications when new features or data are added to the site.

What is Powered By AIDSVu?

Powered By AIDSVu projects use the existing AIDSVu infrastructure to expand to other projects that visualize complex information to inform public health decision making. Powered By AIDSVu projects incorporate collaborative content and programs from additional data sources and partners. The inaugural Powered By AIDSVu project, HIVContinuum.org, was released in February 2015 as a proof of concept and maps the continuum of care across the five stages of the HIV treatment cascade. Now AIDSVu has expanded on this model and maps more than 40 states, Washington, DC, and 35 cities at ZIP Code-level across the U.S. A new Powered By AIDSVu project, HepVu.org, was released in April 2017 and visualizes the first standardized state-level estimates of people with Hepatitis C infection across the United States.

For more information about AIDSVu’s HIV care continuum maps and data, visit the HIV Care Continuum tab.

What does HIVContinuum.org show?

HIVContinuum.org displays data and maps illustrating the HIV care continuum in eight large cities in the U.S. – Atlanta, Chicago, Dallas, New Orleans, New York, Philadelphia, San Francisco, and Washington, D.C and two states – Illinois and Texas. The site includes data for persons newly diagnosed with HIV between 2010 and 2014 and visualizes new HIV diagnosis, late HIV diagnosis, linkage to HIV care, engagement in HIV care, and suppressed HIV Virus (engaged and diagnosed).

These data and maps began as a proof of concept with the inaugural Powered By AIDSVu project HIVContinuum.org in February 2015, and now AIDSVu has expanded on this model to more than 40 states, Washington, DC, and 35 cities at ZIP Code-level across the U.S. For more information about AIDSVu’s HIV care continuum maps and data, visit the HIV Care Continuum tab.

What does HepVu show?

HepVu maps state-level Hepatitis C prevalence estimates obtained from the Emory University Coalition for Applied Modeling for Prevention (CAMP) project, including researchers from the University of Albany. This was a collaborative effort with researchers from the Centers for Disease Control and Prevention (CDC), and findings were published in the peer-reviewed Journal of the American Medical Association (JAMA) Network Open.

HepVu also maps Hepatitis C-related mortality data (2016) and three opioid-related indicators that, together with HepVu’s Hepatitis C data, help illustrate the relationship between the opioid crisis and viral hepatitis in the U.S. The opioid-related data on HepVu include:

• Opioid prescription rate (2017)
• Narcotic overdose mortality rate (2013-2016)
• Pain reliever misuse prevalence (2015-2016)

HepVu’s Hepatitis C data can be visualized by rates and cases, and alongside data comparison maps, including opioid-related indicators and social determinants of health – such as poverty, high school education, median household income, income inequality, and people without health insurance.

Why was AIDSVu developed?

AIDSVu was developed with the goal of making HIV data widely available, easily accessible, and locally relevant to inform public health decision making. AIDSVu’s state-, county-, and city- level data can help increase disease awareness and inform planning and decisions about the best use of HIV prevention, testing, and treatment resources. These data also underscore the importance of all individuals aged 13 to 64 being tested for HIV at least once in their lifetime, as recommended by the U.S. Centers for Disease Control and Prevention (CDC).

Who is AIDSVu intended for?

AIDSVu can be used by everyone. The site is intended to be a resource for public health officials, health care providers, researchers, policymakers, advocates, and the general public. The detailed, yet easily accessible, information on AIDSVu can help communities plan where HIV prevention, testing, and treatment services are needed most; provide important data and visuals for grants, policy reports, and advocacy efforts; and give health care providers and the general public a tool for better understanding how HIV impacts their communities.

Who created AIDSVu?

AIDSVu was developed by Emory University’s Rollins School of Public Health in partnership with Gilead Sciences, Inc. It is led by Dr. Patrick Sullivan, Professor of Epidemiology at Emory University.

Who helps to advise the AIDSVu project?

AIDSVu receives ongoing support and guidance from three groups consisting of key stakeholders and experts: the AIDSVu Advisory Committee, the AIDSVu Technical Advisory Group, and the AIDSVu Prevention and Treatment Advisory Committee. The individuals who participate in these groups are representatives of organizations such as the U.S. Department of Health and Human Services, the U.S. Centers for Disease Control and Prevention, the U.S. National Institutes of Health, the Kaiser Family Foundation, the National Association of State and Territorial AIDS Directors, national patient and community advocates, representatives from state and local health departments, and private industry.

What does AIDSVu’s interactive map show?

AIDSVu visualizes HIV prevalence data – the rates and numbers of persons living with an HIV diagnosis – in states and counties across the U.S. in 2018, and in multiple cities in 2018. The state and county maps also show new HIV diagnoses data – the rates and cases of new HIV diagnoses – from 2008 to 2018. The new HIV diagnoses in the cities show a cumulative 5-year case count and risk from 2014 to 2018. 

AIDSVu also visualizes steps of the HIV care continuum at the state- and city-level for more than 40 states, Washington, DC, and 35 cities. At the state-level, the platform maps late HIV diagnoses (2018), linkage to HIV care (2018), receipt of HIV care (2018), and viral HIV suppression (2018). At the ZIP Code-level, AIDSVu maps late HIV diagnoses (cumulative 2014 to 2018), linkage to HIV care (cumulative 2014 to 2018), receipt of HIV care (2018), and viral HIV suppression (2018). 

The HIV mortality data – the rates and numbers of persons with HIV who died – are shown at the state-level for 2018. AIDSVu also shows PrEP utilization – the rates and numbers of persons using PrEP, or pre-exposure prophylaxis –, as well as  PrEP-to-Need Ratio (PnR) – the ratio of the number of PrEP users in 2018 to the number of people newly diagnosed with HIV in 2017 to serves as a measurement of how PrEP use compares to the need for PrEP in a population –  in states and counties, by year from 2012 to 2018. HIV Testing data – percent of people ever tested for HIV – are shown at the state-level for 2018.

Prevalence and new HIV diagnosis data are available at finer geographic levels, including community area- and census tract- levels for Chicago, census tract-level for Philadelphia, and ward- and census tract-levels for Washington, D.C.

AIDSVu data can be visualized by race/ethnicity, sex, age, and transmission category. HIV data can also be viewed alongside various social determinants of health and related infectious diseases – such as poverty, high school education, median household income, income inequality, people without health insurance, unemployment, housing, food insecurity, Medicaid expansion, as well as Hepatitis C prevalence and primary and secondary syphilis. AIDSVu allows users to locate a place for HIV prevention, testing and care, and also includes NIH-funded HIV prevention, vaccine, and treatment trial locations.

AIDSVu also has local data pages with profiles for more than 45 U.S. cities, 48 counties with the highest burden of new HIV diagnoses that are prioritized for Phase 1 of Ending the HIV Epidemic: A Plan for America initiative, 50 states, DC, Puerto Rico, 4 regions, and the nation, offering easy-to-understand, printable snapshots that summarize the impact of HIV and other sexually transmitted diseases.

What does AIDSVu demonstrate about HIV/AIDS in America?

AIDSVu provides a visualization of the HIV epidemic across the United States. The interactive maps illustrate geographic variations in the HIV epidemic and reveal how the epidemic affects communities differently. This information is important for individuals to understand how HIV impacts their communities, and for health officials and policymakers to see where HIV prevention, testing, and care services are needed most.

How can I get AIDSVu maps and resources for my work?

AIDSVu has a map print functionality, allowing users to download and print custom views from the interactive map for use in grant proposals, presentations, manuscripts, and other materials. Additionally, the local statistics section allows users to download and print state- and city-specific data and fact sheets using a custom export function at the top right-hand side of the page.