About AIDSVu
AIDSVu is a leading free resource for visualizing the HIV epidemic in the United States and seeks to engage and provide users with a highly interactive and easy way to access HIV surveillance data at enhanced geographic levels. AIDSVu currently maps HIV prevalence and new diagnoses data for all U.S. states, all counties in 48 states, Zip Codes in 41 cities, community/ward in 2 cities, and census tracts in 3 cities. At the state level, we also map HIV mortality data and data on PrEP use. All maps are also available to be viewed by demographic breakdowns and can be overlaid with PrEP providers and HIV testing and treatment service locations to enable examination of these resources relative to HIV prevalence and diagnosis data at different geographic levels.
HIV Awareness Day infographics, as well as city and state profile pages provide supplementary visualizations and information and complement the data presented in the maps and existing surveillance reports. Other public data, such as Census data on social determinants of health (i.e. poverty, education, health insurance, etc.) can be viewed as tandem-tethered interactive maps and provide context considering social determinants of health. Downloadable resources include map images, infographic panels that can be used for presentations or other materials, and downloadable datasets. Below you can learn more about the data methods and sources for the state and county data on AIDSVu. Click here to learn more about data methods and sources for Zip Code, census tract, or community area/ward data.
Definitions
HIV Prevalence Data: The data reflect persons living with diagnosed HIV infection or persons living with diagnosed HIV infection ever classified as stage 3 (AIDS) at the end of 2014. The map title “Persons Living with Diagnosed HIV” has been used to encompass persons living with diagnosed HIV and persons living with diagnosed HIV infection ever classified as AIDS. Cases are based on most recent known address.
New HIV Diagnoses Data: The data reflect persons newly diagnosed with HIV infection, defined as a diagnosis of HIV infection regardless of the stage of disease (stage 0, 1, 2, 3 [AIDS], or unknown) and refers to all persons with a diagnosis of HIV infection during a given 1-year time period (i.e. 2015). Multiple single-year data are available from 2008-2015. The map title “Persons Newly Diagnosed with HIV” has been used to encompass persons newly diagnosed with HIV and/or AIDS.
Mortality Data: The data reflect deaths of persons diagnosed with HIV infection or with diagnosed HIV infection classified as stage 3 (AIDS) regardless of the cause of death. The map title “Deaths of Persons Diagnosed with HIV” has been used to encompass deaths of persons diagnosed with HIV and/or AIDS.
PrEP Data: The data reflect the number of unique persons who had at least one day of prescribed oral TDF/FTC for PrEP in a year from 2012 to 2016. Data are described as “Users” for the number of PrEP users and as “Rates” for the number of PrEP users per 100,000 population.
Data Source
HIV Surveillance Data:
The HIV prevalence, new HIV diagnoses, and mortality data presented on AIDSVu are collected by state and local health departments, and de-duplicated and processed by the U.S. Centers for Disease Control and Prevention (CDC) to meet data quality standards for comparability and reliability. All 50 states, the District of Columbia (DC), and U.S. territories collect comparable confidential, name-based case reports of persons living with diagnosed HIV infection. All diagnoses are based on an established case definition. Medical providers, laboratories, and other organizations providing HIV testing services are required, by law, to report persons diagnosed with HIV to the state or local health department. Health departments report case data without names to CDC for monitoring of the national HIV epidemic.
All state- and county-level HIV surveillance data for AIDSVu were obtained from CDC’s national HIV surveillance database housed in the Division of HIV/AIDS Prevention’s HIV Incidence and Case Surveillance Branch in Atlanta, GA. Data were released to AIDSVu by CDC in accordance with HIV-surveillance-specific data re-release agreements between CDC and each state/U.S. territory health department, and in accordance with other CDC data release guidelines. Data reflected on AIDSVu may slightly differ from data obtained directly from state HIV surveillance programs (e.g., on a state health department website or through a data request to a state surveillance program) because states may use analysis criteria that are different from the criteria used by AIDSVu. Further, data on AIDSVu may differ from data obtained directly from the states because AIDSVu’s data source was the CDC’s National HIV Surveillance System, from which duplicate records are removed. In addition to the national data described in these data methods, AIDSVu also displays Zip Code data for 41 jurisdictions (i.e., cities or Metropolitan Statistical Areas or select counties or Zip Codes), with a few cities displaying census tract- and/or community area/ward-level data as well. More information about where these data come from and their presentation on AIDSVu can be found here.
All HIV surveillance data displayed on AIDSVu maps and state profile pages are data for persons aged 13 and older living with diagnosed HIV infection as of December 31, 2014. New HIV diagnoses data include persons aged 13 and older who received a diagnosis of HIV infection between January 1, 2008 and December 31, 2015, displayed year-by-year. Data were reported to CDC through June 2016. Data have been statistically adjusted to account for missing transmission category (See CDC methodology for using multiple imputation assign a transmission category). Most recent known address was used in all analyses except for new HIV diagnoses, which are calculated based on residence at diagnosis. Denominators used to calculate rates for all state and county populations were obtained by the CDC from the U.S. Census Bureau’s census for each respective year. Population denominators are restricted to persons aged 13 and older. There are no county-level maps for Alaska, District of Columbia, and Puerto Rico, because there are no counties in these states.
HIV surveillance data are displayed as case counts and rates, or by proportions for transmission categories (represented as % cases). Rates were calculated per 100,000 population to permit data standardization and comparison. For rate ratios by race/ethnicity displayed on state profile pages, White race is the referent group.
PrEP Data
PrEP data displayed on AIDSVu were obtained from Source Healthcare Analytics, LLC (SHA) with the support of Gilead Sciences, Inc., and compiled by researchers at the Rollins School of Public Health at Emory University. SHA provided Gilead with national, electronic, patient-level prescription data from an overall sample that represents over 54,000 pharmacies, 1,500 hospitals, 800 outpatient facilities, and 80,000 physician practices. This is an open sample of commercially available data, which excludes entities that do not make their data available, such as closed healthcare systems and those that choose not to share their data with SHA. All patient-level prescription data were de-identified and linked to confirmatory data from a de-identified medical insurance claims database. Gilead then utilized a validated algorithm[1] to exclude prescriptions for tenofovir [TDF]/emtricitabine [FTC] that were made for other known indications, such as HIV treatment, post-exposure prophylaxis, and chronic hepatitis B management. This was accomplished by using medical procedure and diagnoses codes also included in the database, and determining the periods when a unique person was exposed to the medication (drug exposure periods per individual, referred to as “PrEP Users”). For each user of TDF/FTC for PrEP, the duration of the PrEP course was determined by examining subsequent renewals of the prescription. A minimum duration of 30 days was required for an individual to be considered a PrEP user, and to be considered a user in a given year, at least 1 day of that 30-day minimum period was required to fall within that calendar year. Finally, the validated, aggregate data were provided to the Rollins School of Public Health, where data suppression rules were applied, and the publicly available maps and data sets for AIDSVu were developed. State-level data were provided for mapping and for download, and ZIP3-level (ZIP3 refers to the three digit Zip code prefix assigned by the U.S. Postal Service) data were provided for download only.
PrEP data are displayed as number of PrEP users and rates. Rates of PrEP use were calculated per 100,000 population to permit data standardization and comparison. American Community Survey (ACS) 1 year population estimates (2012, 2013, 2014, 2015, 2016) were used for the denominator for yearly state-level data. ACS combined 5-year population estimates (2011-2015) were used for the denominator for yearly ZIP3-level data. Denominator totals were for ages 13+, which were obtained from the ACS data by taking the 10-14 age grouping and multiplying by 2/5ths to estimate 13-14 year olds, and then adding with all the other age groups. The denominator totals for the ≤24 age grouping was developed by combining 13-14 (again obtained by multiplying the 10-14 age grouping by 2/5ths), 15-19 and 18-24, to create one age category of 24 or less.
Data Suppression and Rate Stability
For HIV data the following data suppression rules were applied:
To protect the privacy of persons living with diagnosed HIV infection, AIDSVu does not display rates and case counts for states and/or counties when one or more of the following suppression criteria are met:
- Numerator (number of persons living with diagnosed HIV infection) is less than 5 at the county-level and/or the denominator (number of people in the county in that population group) is less than 100. If the overall county case count is less than 5 and/or the overall county population is less than 100, all data for the county are suppressed
- For breakdowns by sex at the county-level, if either the male or female rate and/or case count is suppressed because of the numerator/denominator thresholds mentioned in #1, both sex groups are suppressed to prevent indirect identification.
- For breakdowns by age at the county-level, if the rate and/or case count for only one age group is suppressed in a county because of the numerator/denominator thresholds mentioned in #1, then the 13-24 age group is also suppressed to prevent indirect identification. If the 13-24 age group is the only age group suppressed for a county, then the 55+ age group is also suppressed.
- If data for only one county in a state is suppressed, then one additional county is also suppressed, with the additional county selected based on having the smallest total population of the remaining counties. In the event there are multiple counties in a state with the exact same total population, the county with the lowest number of HIV cases is also suppressed. In the event there are multiple counties in a state with the same total population and the same total number of HIV cases, then both or all of these counties are suppressed.
States and counties are noted by the color white when one or more of these conditions are met. As is standard in the display of health statistics, rates generated from a numerator less than 12 are considered unstable and should be interpreted with caution. Because rates at the county-level are not displayed when the numerator is less than 5, the “unreliable rate” indicator will only display when the numerator is 5 or greater and less than 12.
For year-by-year new HIV diagnoses data, if the overall county case count breakdown is less than 5, all data for the county are suppressed.
[1] 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.
For ZIP3 PrEP data in the downloadable dataset, the following data suppression rules were applied:
To protect the privacy of people using PrEP, AIDSVu will not display PrEP data for states or at the ZIP3 unit-level when one or more of the following suppression criteria are met:
- The number of persons using PrEP is less than 3 at the ZIP3 unit-level and/or the denominator (number of people in the ZIP3 unit in that population group) is less than 100. If the overall ZIP3 unit has less than 3 PrEP users and/or the overall ZIP3 unit population is less than 100, all data for the ZIP3 unit are suppressed.
- For breakdowns by sex at the ZIP3 unit-level, if either the male or female PrEP data are suppressed because of the numerator/denominator thresholds mentioned in #1, both sex groups are suppressed to prevent indirect identification.
- For breakdowns by age at the ZIP3 unit-level, if the PrEP data for only one age group are suppressed in a ZIP3 unit because of the numerator/denominator thresholds mentioned in #1, then the ≤24 age group is also suppressed to prevent indirect identification. If the ≤24 age group is the only age group suppressed for a ZIP3 unit, then the 55+ age group is also suppressed.
- If data for only one ZIP3 unit in a state is suppressed, then one additional ZIP3 unit is also suppressed, with the additional ZIP3 unit selected based on having the smallest total population of the remaining ZIP3 unit.
States and ZIP3s are noted by the color white when one or more of these conditions are met. As is standard in the display of health statistics, rates generated from a numerator less than 12 are considered unstable and should be interpreted with caution. Because rates at the ZIP3-level are not displayed when the numerator is less than 3, the “unreliable rate” indicator will only display when the numerator is 3 or greater and less than 12.
Data Stratification
AIDSVu allows viewers to look at HIV surveillance data at the overall geographic level, and by race/ethnicity, sex, and age groups. Additionally, AIDSVu displays transmission categories with two-way stratification possibilities at the state level for both prevalence and new HIV diagnoses. The county-level HIV prevalence data includes one-way transmission categories in addition to the other demographic data. All race groups are non-Hispanic, and the Hispanic/Latino ethnicity is inclusive of all races. Sex is defined as “sex at birth.” Cases were assigned to age groups based on “age at the end of 2014.”
The PrEP data can be stratified by age and sex. Age is defined as “year at birth” and displayed as 24 and under (13-24), 25 to 34, 35 to 44, 45 to 54, 55+. Sex is defined as “sex at birth”.
Caution should be exercised when viewing and interpreting these different maps because the scales change across the different demographic breakdowns and geographic levels.
Data Caveats
HIV Surveillance Data:
HIV data are displayed only for black, white, and Hispanic/Latino persons at the county level because data for Asian, Native Hawaiian/Other Pacific Islander, Multiple Race, and American Indian/Alaska Native persons do not meet CDC’s criteria for statistical reliability, data quality, or confidentiality due to small population denominators or small HIV case counts. Race/ethnicity data for Puerto Rico is displayed only by case counts and not by rate.
New HIV diagnoses data are displayed only for overall rates and cases and not for any race/ethnicity, sex, or age groups at the county level.
Due to the data re-release agreement between the state and CDC, South Dakota does not display county-level HIV data.
PrEP Data:
PrEP data cannot be stratified by race/ethnicity.
There is currently no single data source that includes data on all unique users of PrEP across the U.S. Source Healthcare Analytics (SHA) collects data from over 54,000 pharmacies, 1,500 hospitals, 800 outpatient facilities, and 80,000 physician practices across the U.S. SHA’s dataset contains prescription, medical, and hospital claims data for all payment types, including commercial plans, Medicare Part D, cash, assistance programs, and Medicaid. From this overall sample, AIDSVu presents a subset of data comprising prescriptions for TDF/FTC for PrEP.
SHA’s dataset is an open sample of commercially available data, which excludes entities that do not make their data available, such as closed healthcare systems and entities that choose not to share their data with SHA. As a result, this dataset underestimates the total number of PrEP users in the U.S.
Medical procedure and diagnosis code data were not available for 28% of the SHA records. These procedure and diagnosis codes are required to determine whether an individual TDF/FTC prescription was made for PrEP, for treatment of HIV or Hepatitis B infection, or was used for post-exposure prophylaxis (PEP). These 28% of records were assumed to not represent TDF/FTC prescriptions for PrEP, although some proportion of these records were likely, in reality, PrEP prescriptions. This is a further source of underestimation of PrEP users.
Data are derived from prescriptions to unique people; however, those who fill a prescription may not use it.
Additionally, the overall total population may be fewer than the sum of age group total population for a given year because people may be counted twice if they switch age groups within a certain year (i.e. if a person turns 35 in 2016 then the person is counted in both the 25-34 and 35-44 age groups in 2016).
Ranges/Legend Values
Range intervals were initially developed using deciles in SAS analytic software (SAS Institute, Cary, NC). Set cut points were derived using rounded deciles from the previous year, when previous year data were available. When previous year deciles were not available, rounded current year deciles were used for data new to this release. In order to illustrate the variation in the data, ranges were developed specific to each geographic level (i.e., states or counties), for each one-way grouping (i.e., overall, separately by race, by sex, by age group and by transmission category), and for each two-way group combination (i.e., by sex and age group, by sex and race, by sex and transmission category, etc.), when data were available.
Thus, for state prevalence and new HIV diagnoses maps, a total of 19 sets of map scales exist for each (rate/count by overall/race/sex/age/two-way, proportion/case by transmission category and age/transmission category and sex/transmission category and race, and transmission category total case counts for heterosexual, IDU, and other). For state mortality, there are 15 sets of scales (rate/count by overall/race/sex/age and proportion/case by male/female transmission category, and transmission category total case counts for heterosexual, IDU, and other). A total of eight sets of map scales exist for county-level prevalence data (rate/count by overall/race/sex/age and proportion/case by male/female transmission category). A total of six map scales exist for state-level PrEP data (users/rates by overall/sex/age).
For each scale calculation, the original deciles used to create the rounded set cut points were determined by combining the individual rates or counts for all areas with data included on the maps for that geographic level and demographic grouping.
Social Determinants of Health
Social determinants of health are displayed on a secondary map and their associated scales were developed using the same method as above. Therefore, there are 5 additional ranges for both state- and county-level data. The five social determinants displayed are: poverty (percent of population living in poverty), high school education (percent of population with a high school degree or equivalent), median household income, income inequality (measured by the Gini Coefficient, a measure of income inequality where 0 reflects complete equality and 1 reflects complete inequality), and people without health insurance (percent of population lacking health insurance).
Corrections Warning
The HIV prevalence and new diagnoses data displayed on AIDSVu include state and federal correctional populations. Their inclusion may artificially inflate the HIV prevalence rate and case count of counties that house institutions. A correctional warning is displayed in the map hover-over balloon of certain counties when artificial inflation may be present based on predefined criteria.
To determine in which counties the correctional warning should appear, the following process and predefined thresholds were used to categorize counties.
- All U.S. counties were categorized by level of urbanization using the National Center for Health Statistics (NCHS) Urban-Rural Classification Scheme.
- Federal and state correction populations were obtained for each county from the 2010 U.S. Census.
- Within these strata of urbanization, counties are assigned the corrections warning if they had:
- Above average HIV prevalence rate (as compared to counties with no correctional population)
- Above average correctional population or above average percent of the population housed in state/federal correctional institutions
AND
Static Maps
HIV Ever Tested data from the BRFSS were obtained from the CDC’s State HIV Prevention Progress Report, 2010-2013, which was released in December 2015. People aged 18-64 years were asked the question, “Have you ever been tested for HIV? Do not count tests you may have had as part of a blood donation. Include testing fluid from your mouth.”
Medicaid Expansion data were obtained from the Kaiser Family Foundation’s “Status of State Action on the Medicaid Expansion Decision,” KFF State Health Facts, updated July 7, 2016.
Downloadable Datasets
National data for state, county, and ZIP3 are available for download. The latest state data are available for 2008-2015 HIV New Diagnoses, 2014 HIV Prevalence and Mortality, and 2012-2016 PrEP utilization. The latest county data are available for 2008-2015 HIV New Diagnoses and 2014 HIV Prevalence. The latest ZIP3 data are available for 2012-2016 PrEP utilization.
Citation
Data, maps, and information from AIDSVu may be used, provided credit is given to AIDSVu and the Rollins School of Public Health at Emory University. Recommended citations:
Data Source: AIDSVu (www.aidsvu.org). Emory University, Rollins School of Public Health.
Data Sources
Surveillance Data
| Data Element | Location on AIDSVu | Data Source | Anticipated Update Frequency on AIDSVu Website |
| Rates and Case Counts of Persons Living with Diagnosed HIV, 2014, State & County Data | Maps; Downloadable Datasets | Centers for Disease Control and Prevention, Division of HIV/AIDS Prevention, HIV Incidence and Case Surveillance Branch; Data Request, January 2017. | Annually |
| Year-by-year Rates and Case Counts of Persons Newly Diagnosed with HIV, 2008-2015, State & County Data | Maps; Downloadable Datasets | Centers for Disease Control and Prevention, Division of HIV/AIDS Prevention, HIV Incidence and Case Surveillance Branch; Data Request, January 2017. | Annually |
| Rates and Case Counts of Deaths of Persons with Diagnosed HIV, 2014, State Data | Maps; Downloadable Datasets | Centers for Disease Control and Prevention, Division of HIV/AIDS Prevention, HIV Incidence and Case Surveillance Branch; Data Request, January 2017. | Annually |
| Percent Late HIV Infection Diagnoses | State Profile Pages | Centers for Disease Control and Prevention, Division of HIV/AIDS Prevention, HIV Incidence and Case Surveillance Branch; Data Request, January 2017. | Annually |
| HIV Prevalence Rate Ratios by Race/Ethnicity | State Profile Pages | Centers for Disease Control and Prevention, Division of HIV/AIDS Prevention, HIV Incidence and Case Surveillance Branch; Data Request, January 2017. | Annually |
| HIV Prevalence Case Counts and Percentages by Transmission Category, State & County Level | Maps; State Profile Pages; Downloadable Datasets | Centers for Disease Control and Prevention, Division of HIV/AIDS Prevention, HIV Incidence and Case Surveillance Branch; Data Request, January 2017. | Annually |
| STD Case Counts and Rates | State Profile Pages | Centers for Disease Control and Prevention. Sexually Transmitted Disease ATLAS website. | Annually |
| Age-Adjusted HIV Mortality Rates, 2011-2013 | State Profile Pages | Centers for Disease Control and Prevention; National Center for Health Statistics. Compressed Mortality File (CMF) on CDC WONDER Online Database, 1999-2015. | Annually |
| State Progress Toward CDC’s Division of HIV/AIDS Prevention Goals for 2015 | State Profile Pages | Centers for Disease Control and Prevention; HIV Surveillance Supplemental Report, 2014. | Annually |
| Rates and Numbers of Persons Using PrEP, 2012-2016, State Data | Maps; Downloadable Datasets | Source Healthcare Analytics, LLC and Gilead Sciences, Inc.; Data Request, December 2017. | As Available |
| Rates and Numbers of Persons Using PrEP, 2012-2016, ZIP3 Data | Downloadable Datasets | Source Healthcare Analytics, LLC and Gilead Sciences, Inc.; Data Request, December 2017. | As Available |
Service Locators and Federal Funding for HIV/AIDS
| Data Element | Location on AIDSVu | Data Source | Anticipated Update Frequency on AIDSVu Website |
| HIV Testing Sites | Maps; HIV Testing Site Locator | Centers for Disease Control and Prevention, National Prevention Information Network; Ongoing Data Access Request. | Annually |
| Ryan White HIV/AIDS Medical Care Providers | Maps; HIV Treatment Site Locator | Health Resources and Services Administration, HIV/AIDS Bureau; Ongoing Data Access Request. | Annually |
| PrEP Locator | Maps; PrEP Locator | Emory University, Rollins School of Public Health; preplocator.org. | Annually |
| NIH-Funded HIV Prevention, Vaccine and Treatment Trials Sites | Maps | National Institutes of Health, National Institute of Allergy and Infectious Diseases, Division of AIDS; Ongoing Data Access Request. | Annually |
| Federal Grant Funding for HIV/AIDS, FY 2015 | State Profile Pages | Kaiser Family Foundation. State Health Facts. | Annually |
| Housing Opportunities for People with AIDS | Maps | U.S. Department of Housing & Urban Development, Office of Community Planning and Development; Ongoing Data Access Request. | Annually |
State Health Department Websites
| Data Element | Location on AIDSVu | Data Source | Anticipated Update Frequency on AIDSVu Website |
| State Health Department Websites | State Profile Pages | State health departments and internet. | Annually |
Policy Maps
| Data Element | Location on AIDSVu | Data Source | Anticipated Update Frequency on AIDSVu Website |
| HIV Ever Tested, 2013 | AIDSVu in Use | BRFSS Data from the Centers for Disease Control and Prevention; HIV Prevention State Progress Reports, 2015. | Annually |
| Medicaid Expansion | AIDSVu in Use | “Status of State Action on the Medicaid Expansion Decision,” KFF State Health Facts, updated July 7, 2016 | Annually |
