Core Indicators for Monitoring EHE: National HIV Surveillance (NHSS) Data reported to CDC through September 2020; PrEP data reported through June 2020
Core Indicators for Monitoring the Ending the HIV Epidemic Initiative (Preliminary Data) : HIV Diagnoses and Linkage to HIV Medical Care, 2019 and 2020 (Reported through September 2020); and Preexposure Prophylaxis (PrEP), 2018 (Updated), 2019 and 2020 (Reported through June 2020)
This issue of HIV Surveillance Data Tables is published by the Division of HIV/AIDS Prevention (DHAP), National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention, Centers for Disease Control and Prevention (CDC), U.S. Department of Health and Human Services, Atlanta, Georgia.
Data are presented for diagnoses of HIV infection reported to CDC through September 2020.
HIV Surveillance Data Tables is not copyrighted and may be used and copied without permission. Citation of the source is, however, appreciated.
Suggested Citation
Centers for Disease Control and Prevention. Core indicators for monitoring the Ending the HIV Epidemic initiative (preliminary data): HIV diagnoses and linkage to HIV medical care, 2019 and 2020 (reported through September 2020); and preexposure prophylaxis (PrEP), 2018 (updated), 2019 and 2020 (reported through June 2020). HIV Surveillance Data Tables 2021;2(No. 1). http://www.cdc.gov/hiv/library/reports/surveillance-data-tables/vol-1-no-7/index.html. Published February 2021. Accessed [date]
Report volume and number updated February 2021.
The Ending the HIV Epidemic: A Plan for America (EHE) initiative will leverage critical scientific advances in HIV prevention, diagnosis, treatment, and outbreak response [1]. The goal of the initiative is to reduce new HIV infections by 75% in 5 years and by at least 90% in 10 years. Throughout the initiative, the Centers for Disease Control and Prevention (CDC) will routinely release HIV Surveillance Data Tables on the 6 core indicators for EHE to allow for more timely monitoring of progress. The full list of EHE core indicators and their definitions can be found in the Technical Notes of the Core Indicators for Monitoring the Ending the HIV Epidemic Initiative report at https://www.cdc.gov/hiv/library/reports/surveillance-data-tables/vol-1-no-1/index.html.
The tables included in this report provide preliminary data on HIV diagnoses and linkage to HIV medical care reported to CDC as of September 2020 for the years 2019 and 2020, and data on preexposure prophylaxis (PrEP) coverage for the year 2018 (updated), 2019 and 2020 (preliminary). Data for the 3 indicators are provided at the national-, state-, and county-levels (EHE Phase I jurisdictions only). See Tabulation and Presentation of Data for details on how the indicators are calculated. Data reported to the National HIV Surveillance System (NHSS) are considered preliminary until a 12-month reporting lag has been reached. Because the data in this report are provided by using an NHSS dataset produced prior to reaching a 12-month reporting lag, the data should be interpreted with caution. In addition to being preliminary, data for the year 2020 should be interpreted with caution due to the impact of the COVID-19 pandemic on HIV case surveillance activities in state/local jurisdictions [2].
Tabulation and Presentation of Data
Diagnosis of HIV Infection
Diagnoses of HIV infection are the numbers of persons aged ≥13 years whose HIV infection was diagnosed during January 2019 through September 2020 (Tables 1a–d).
Data presented were reported (after the removal of personally identifiable information) to CDC’s NHSS through September 2020. Please use caution when interpreting data on diagnoses of HIV infection. HIV surveillance reports may not be representative of all persons with HIV because not all infected persons have been (1) tested or (2) tested at a time when the infection could be detected and diagnosed. Also, some states offer anonymous HIV testing; the results of anonymous tests are not reported to the confidential, name-based HIV registries of state and local health departments. Therefore, reports of confidential test results may not represent all persons who tested positive for HIV infection.
Data reported to NHSS are considered preliminary until a 12-month reporting lag has been reached and should be interpreted with caution. In addition to being preliminary, data for the year 2020 should be interpreted with caution due to the impact of the COVID-19 pandemic on HIV case surveillance activities in state and local jurisdictions.
More information on counting diagnoses of HIV infection can be found at https://www.cdc.gov/hiv/library/reports/hiv-surveillance/vol-31/index.html (HIV Surveillance Report, 2018 [Updated]).
Linkage to HIV Medical Care
Linkage to HIV medical care within 1 month of HIV diagnosis is measured for persons aged ≥13 years whose HIV infection was diagnosed during January 2019 through June 2020, and who resided in any of the jurisdictions (including EHE Phase I jurisdictions) with complete reporting of laboratory data to CDC at the time of diagnosis (Tables 2a–c). The numerator is the number of persons aged ≥13 years whose HIV infection was diagnosed during the specified period and who had ≥1 CD4 or viral load (VL) test within 1 month of HIV diagnosis. The denominator is the number of persons aged ≥13 years whose HIV infection was diagnosed during the specified period. Reporting of linkage to HIV medical care data requires a minimum 3-month reporting lag to account for delays in reporting of laboratory results to NHSS; therefore, data for the year 2020 on linkage to HIV medical care in these surveillance tables are for persons with HIV diagnosed during January through June of 2020 and that were reported to NHSS through September 2020. Data are not provided for states and associated jurisdictions that do not have laws requiring reporting of all CD4 and viral loads, or that have incomplete reporting of laboratory data to CDC. Areas without laws: Idaho, New Jersey, and Pennsylvania. Areas with incomplete reporting: Arizona, Arkansas, Connecticut, Kansas, Kentucky, Vermont, and Puerto Rico.
Data reported to NHSS are considered preliminary until a 12-month reporting lag has been reached and should be interpreted with caution. In addition to being preliminary, data for the year 2020 should be interpreted with caution due to the impact of the COVID-19 pandemic on HIV case surveillance activities in state and local jurisdictions.
More information on calculating linkage to care can be found at Monitoring selected national HIV prevention and care objectives by using HIV surveillance data—United States and 6 dependent areas, 2018 [PDF – 4 MB].pdf icon
Preexposure Prophylaxis (PrEP) Coverage
PrEP coverage, reported as a percentage, is defined as the number of persons aged ≥16 years classified as having been prescribed PrEP during the specified year divided by the estimated number of persons aged ≥16 years who had indications for PrEP during the specified year (Tables 3a–c).
Number of persons prescribed, which is reported as a case count, is defined as the number of persons aged ≥16 years classified as having been prescribed PrEP during the specified year.
PrEP coverage is an EHE indicator that is not a reportable disease or condition and is not reported to NHSS. Multiple data sources, described below, are used to calculate PrEP coverage. Please use caution when interpreting PrEP data. Different data sources were used in the numerator and denominator to calculate PrEP coverage.
Persons Prescribed PrEP
National pharmacy data from the IQVIA Real World Data-Longitudinal Prescriptions database (hereafter, IQVIA database) are used to classify persons aged ≥16 years who have been prescribed PrEP in the specific year. The IQVIA database captures prescriptions from all payers and represents approximately 92% of all prescriptions from retail pharmacies and 60%–86% from mail-order outlets in the United States. The database does not include prescriptions from some closed health care systems that do not make their prescription data available to IQVIA. Therefore, these are minimum estimates of PrEP coverage. The annual number of persons classified as having been prescribed PrEP was based on a validated algorithm that discerns whether tenofovir disoproxil fumarate and emtricitabine (TDF/FTC) were prescribed for PrEP after excluding prescriptions for HIV treatment, hepatitis B treatment, or HIV postexposure prophylaxis [3–5]. Tenofovir alafenamide and emtricitabine (TAF/FTC) was approved as an alternative drug for PrEP by the FDA in October 2019. Starting 2019, TAF/FTC was included in the algorithm to estimate number of persons prescribed PrEP.
The number of persons classified as having been prescribed PrEP is reported by sex, age group, and race/ethnicity. Transmission category data are not available in the IQVIA database and race/ethnicity data are available for <40% of persons with PrEP prescriptions. Please use caution when interpreting PrEP data by race/ethnicity. Race/ethnicity categories available in the IQVIA data include white, black/African American, Hispanic/Latino, and Asian/other. The number of persons prescribed PrEP for each racial/ethnic group presented was extrapolated by applying the racial/ethnic distribution of known records to those for which data on race/ethnicity was unknown.
Geographic Designations
In the IQVIA database, a person’s location is reported as a 3-digit ZIP code prefix (hereafter, ZIP3) assigned by the U.S. Postal Service. To estimate the number of persons prescribed PrEP at the state or county level, a probability-based approach is used to crosswalk between ZIP3s and states/counties using data from (a) the U.S Census Bureau’s American Community Survey (ACS) 5-year estimates by ZIP Code Tabulation Areas (ZCTAs) [6], and (b) the U.S Department of Housing and Urban Development’s ZIP Code Crosswalk Files [7]. Because of reliability concerns, subnational estimates of <40 are not included.
Persons with PrEP Indications
U.S. Census Bureau datasets were used to estimate the number of men who have sex with men (MSM) in a jurisdiction. Next, behavioral data from the National Health and Nutrition Examination Survey (NHANES) were used to estimate the proportion of HIV-negative MSM with indications for PrEP [8]. For the 2018 denominator, this proportion was updated with recent NHANES data.
The number of HIV-negative MSM with indications for PrEP was multiplied by the ratio of percentage of HIV diagnoses during the specified year attributed to other major transmission risk groups compared to the percentage among MSM in a given state or county. The estimated numbers of persons with indications for PrEP in the 3 major transmission risk groups (MSM, heterosexuals, persons who inject drugs) in each jurisdiction were then summed to yield a state- or county-specific estimate. State estimates were then summed for a national total of persons with indications for PrEP [8]. Jurisdictional estimates were rounded to the nearest 10. Beginning in 2018, methods were adjusted to provide the estimated number of Asians and persons of other race ethnicities in addition to Black/African Americans, Hispanic/Latino, and white persons.
The tables included in this report provide updated data on PrEP coverage for the year 2018, and preliminary data for the years 2019 and 2020 (from January through June) using the IQVIA data reported through June 2020. The data sources used to estimate the number of persons with indications for PrEP have different schedules of data availability. Consequently, the availability of a denominator lags the availability of a numerator by approximately 1 year. For this release of the HIV Surveillance Data Tables, 2018 denominators were used for 2018, 2019 and 2020 PrEP coverage data.
References
- HHS. What is ‘Ending the HIV Epidemic: A Plan for America’? https://www.hiv.gov/federal-response/ending-the-hiv-epidemic/overviewexternal icon. Published October 4, 2019. Accessed July 13, 2020.
- CDC [Schuchat A, CDC COVID-19 Response Team]. Public Health Response to the Initiation and Spread of Pandemic COVID-19 in the United States, February 24–April 21, 2020. MMWR 2020;69(18):551–556. doi:http://dx.doi.org/10.15585/mmwr.mm6918e2external icon
- Wu H, Mendoza MC, Huang YA, Hayes T, Smith DK, Hoover KW. Uptake of HIV pre-exposure prophylaxis among commercially insured persons—United States, 2010–2014. Clin Infect Dis 2017;64(2):144–149. doi:10.1093/cid/ciw701.
- CDC [Huang YA, Zhu W, Smith DK, Harris N, Hoover KW]. HIV pre-exposure prophylaxis, by race and ethnicity—United States, 2014–2016. MMWR 2018;67(41):1147–1150. doi:10.15585/mmwr.mm6741a3.
- Furukawa NW, Smith DK, Gonzalez CJ, et al. Evaluation of algorithms used for PrEP surveillance using a reference population from New York City, July 2016–June 2018. Public Health Rep 2020;135(2):202–210. doi:10.1177/0033354920904085
- U.S. Census Bureau. American Community Survey 5-year data (2009-2018). https://www.census.gov/data/developers/data-sets/acs-5year.2018.htmlexternal icon. Published December 19, 2019. Accessed July 13, 2020.
- HUD. HUD USPS ZIP code crosswalk files. https://www.huduser.gov/portal/datasets/usps_crosswalk.htmlexternal icon. Published 2019. Accessed July 13, 2020.
- CDC [Smith DK, Van Handel M, Wolitski RJ, et al]. Vital Signs: Estimated percentages and numbers of adults with indications for pre-exposure prophylaxis to prevent HIV acquisition—United States, 2015. MMWR 2015;64(46):1291–1295. doi:10.15585/mmwr.mm6446a4.
Suggested Citation
Centers for Disease Control and Prevention. Core indicators for monitoring the Ending the HIV Epidemic initiative (preliminary data): HIV diagnoses and linkage to HIV medical care, 2019 and 2020 (reported through September 2020); and preexposure prophylaxis (PrEP), 2018 (updated), 2019 and 2020 (reported through June 2020). HIV Surveillance Data Tables 2021;2(No. 1). http://www.cdc.gov/hiv/library/reports/surveillance-data-tables/vol-1-no-7/index.html. Published February 2021. Accessed [date]
Acknowledgments
Publication of HIV Surveillance Data Tables was made possible by the contributions of the state and territorial health departments and the HIV surveillance programs that provided surveillance data to CDC.
HIV Surveillance Data Tables was prepared by the following staff and contractors of the Division of HIV/AIDS Prevention, National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention, CDC: Anna Satcher Johnson, Zanetta Gant, Ya-lin Huang, Dawn Smith, Xiaohong Hu, Jianmin Li, Baohua Wu, Chan Jin, Shihua Wang, Weiming Zhu, Anne Patala, Lei Yu, Norma Harris, and Michael Friend and the Web and Consumer Services Team of the Prevention Communications Branch (editing and desktop publishing).
| 2019 | 2020 (January – September) | |
|---|---|---|
| Total No. | Total No. | |
| Gender | ||
| Male | 28,469 | 13,635 |
| Female | 6,784 | 3,191 |
| Transgender male-to-femalea | 610 | 273 |
| Transgender female-to-malea | 42 | 17 |
| Additional gender identityb | 19 | 6 |
| Age at diagnosis (yr) | ||
| 13–24 | 7,483 | 3,419 |
| 25–34 | 12,902 | 6,238 |
| 35–44 | 6,993 | 3,269 |
| 45–54 | 4,811 | 2,321 |
| ≥55 | 3,735 | 1,875 |
| Race/ethnicity | ||
| American Indian/Alaska Native | 206 | 105 |
| Asian | 731 | 364 |
| Black/African American | 15,409 | 7,672 |
| Hispanic/Latinoc | 9,574 | 4,131 |
| Native Hawaiian/other Pacific Islander | 65 | 37 |
| White | 9,055 | 4,525 |
| Multiple races | 884 | 288 |
| Transmission categoryd | ||
| Male-to-male sexual contact | 23,724 | 11,552 |
| Injection drug use | ||
| Male | 1,353 | 674 |
| Female | 1,094 | 477 |
| Male-to-male sexual contact and injection drug use | 1,426 | 553 |
| Heterosexual contacte | ||
| Male | 2,558 | 1,115 |
| Female | 5,708 | 2,714 |
| Otherf | ||
| Male | 34 | 19 |
| Female | 28 | 18 |
| Region of residenceg | ||
| Northeast | 5,242 | 2,326 |
| Midwest | 4,725 | 2,255 |
| South | 18,868 | 9,419 |
| West | 7,089 | 3,122 |
| Total | 35,924 | 17,122 |
Abbreviations: CDC, the Centers for Disease Control and Prevention [footnotes only].
Note. Data are for cases reported to CDC through September 2020, are considered preliminary until a 12-month reporting lag has been reached, and should be interpreted with caution. In addition to being preliminary, data for the year 2020 should be interpreted with caution due to the impact of the COVID-19 pandemic on HIV case surveillance activities in state/local jurisdictions.
aTransgender male-to-female” includes individuals who were assigned “male” sex at birth but have ever identified as “female” gender. “Transgender female-to-male” includes individuals who were assigned “female” sex at birth but have ever identified as “male” gender.
bAdditional gender identity examples include “bigender,” “gender queer,” and “two-spirit.”
cHispanics/Latinos can be of any race.
dData have been statistically adjusted to account for missing transmission category, therefore values may not sum to column subtotals and total. Data presented based on sex at birth and may include transgender persons.
eHeterosexual contact with a person known to have, or to be at high risk for, HIV infection.
fIncludes hemophilia, blood transfusion, perinatal exposure, and risk factor not reported or not identified.
gData are based on residence at time of diagnosis of HIV infection.
| 2019 | 2020 (January – June) | |
|---|---|---|
| Total No. | Total No. | |
| Gender | ||
| Male | 28,789 | 13,766 |
| Female | 6,864 | 3,217 |
| Transgender male-to-femalea | 612 | 274 |
| Transgender female-to-malea | 42 | 17 |
| Additional gender identityb | 19 | 6 |
| Age at diagnosis (yr) | ||
| 13–24 | 7,543 | 3,451 |
| 25–34 | 13,014 | 6,277 |
| 35–44 | 7,071 | 3,304 |
| 45–54 | 4,877 | 2,346 |
| ≥55 | 3,821 | 1,902 |
| Race/ethnicity | ||
| American Indian/Alaska Native | 206 | 105 |
| Asian | 737 | 364 |
| Black/African American | 15,414 | 7,674 |
| Hispanic/Latinoc | 9,954 | 4,283 |
| Native Hawaiian/other Pacific Islander | 69 | 37 |
| White | 9,062 | 4,529 |
| Multiple races | 884 | 288 |
| Transmission categoryd | ||
| Male-to-male sexual contact | 23,944 | 11,649 |
| Injection drug use | ||
| Male | 1,376 | 687 |
| Female | 1,099 | 478 |
| Male-to-male sexual contact and injection drug use | 1,438 | 558 |
| Heterosexual contacte | ||
| Male | 2,624 | 1,132 |
| Female | 5,783 | 2,738 |
| Otherf | ||
| Male | 34 | 19 |
| Female | 28 | 18 |
| Region of residenceg | ||
| Northeast | 5,242 | 2,326 |
| Midwest | 4,725 | 2,255 |
| South | 18,868 | 9,419 |
| West | 7,089 | 3,122 |
| U.S. dependent areas | 402 | 158 |
| Total | 36,326 | 17,280 |
Abbreviations: CDC, the Centers for Disease Control and Prevention [footnotes only].
Note. Data are for cases reported to CDC through September 2020, are considered preliminary until a 12-month reporting lag has been reached, and should be interpreted with caution. In addition to being preliminary, data for the year 2020 should be interpreted with caution due to the impact of the COVID-19 pandemic on HIV case surveillance activities in state/local jurisdictions.
aTransgender male-to-female” includes individuals who were assigned “male” sex at birth but have ever identified as “female” gender. “Transgender female-to-male” includes individuals who were assigned “female” sex at birth but have ever identified as “male” gender.
bAdditional gender identity examples include “bigender,” “gender queer,” and “two-spirit.”
cHispanics/Latinos can be of any race.
dData have been statistically adjusted to account for missing transmission category, therefore values may not sum to column subtotals and total. Data presented based on sex at birth and may include transgender persons.
eHeterosexual contact with a person known to have, or to be at high risk for, HIV infection.
fIncludes hemophilia, blood transfusion, perinatal exposure, and risk factor not reported or not identified.
gData are based on residence at time of diagnosis of HIV infection.
| 2019 | 2020 (January – September) | |
|---|---|---|
| Area of residence | Total No. | Total No. |
| Alabama | 640 | 346 |
| Alaska | 27 | 22 |
| Arizona | 765 | 421 |
| Arkansas | 285 | 193 |
| California | 4,230 | 1,746 |
| Colorado | 460 | 211 |
| Connecticut | 207 | 83 |
| Delaware | 93 | 70 |
| District of Columbia | 247 | 112 |
| Florida | 4,402 | 2,535 |
| Georgia | 2,315 | 1,058 |
| Hawaii | 65 | 23 |
| Idaho | 27 | 2 |
| Illinois | 1,238 | 441 |
| Indiana | 485 | 257 |
| Iowa | 100 | 65 |
| Kansas | 132 | 74 |
| Kentucky | 314 | 150 |
| Louisiana | 887 | 499 |
| Maine | 30 | 12 |
| Maryland | 926 | 441 |
| Massachusetts | 536 | 216 |
| Michigan | 675 | 370 |
| Minnesota | 274 | 146 |
| Mississippi | 477 | 270 |
| Missouri | 489 | 245 |
| Montana | 26 | 3 |
| Nebraska | 81 | 34 |
| Nevada | 510 | 156 |
| New Hampshire | 30 | 15 |
| New Jersey | 1,035 | 388 |
| New Mexico | 147 | 42 |
| New York | 2,332 | 1,127 |
| North Carolina | 1,370 | 748 |
| North Dakota | 36 | 11 |
| Ohio | 975 | 479 |
| Oklahoma | 309 | 121 |
| Oregon | 198 | 115 |
| Pennsylvania | 989 | 456 |
| Rhode Island | 72 | 22 |
| South Carolina | 688 | 466 |
| South Dakota | 33 | 12 |
| Tennessee | 768 | 428 |
| Texas | 4,176 | 1,452 |
| Utah | 136 | 96 |
| Vermont | 11 | 7 |
| Virginia | 827 | 440 |
| Washington | 485 | 278 |
| West Virginia | 144 | 90 |
| Wisconsin | 207 | 121 |
| Wyoming | 13 | 7 |
| Subtotal | 35,924 | 17,122 |
| U.S. dependent areas | ||
| American Samoa | 0 | 0 |
| Guam | 10 | 0 |
| Northern Mariana Islands | 2 | 0 |
| Puerto Rico | 383 | 156 |
| Republic of Palau | 0 | 0 |
| U.S. Virgin Islands | 7 | 2 |
| Subtotal | 402 | 158 |
| Total | 36,326 | 17,280 |
Abbreviations: CDC, the Centers for Disease Control and Prevention [footnotes only].
Note. Data are based on residence at time of diagnosis of HIV infection. Data are for cases reported to CDC through September 2020, are considered preliminary until a 12-month reporting lag has been reached, and should be interpreted with caution. In addition to being preliminary, data for the year 2020 should be interpreted with caution due to the impact of the COVID-19 pandemic on HIV case surveillance activities in state/local jurisdictions.
| 2019 | 2020 (January – September) | |
|---|---|---|
| Area of residence | Total No. | Total No. |
| Arizona | ||
| Maricopa County | 517 | 304 |
| California | ||
| Alameda County | 220 | 105 |
| Los Angeles County | 1,447 | 618 |
| Orange County | 246 | 178 |
| Riverside County | 262 | 127 |
| Sacramento County | 86 | 6 |
| San Bernardino County | 271 | 51 |
| San Diego County | 360 | 76 |
| San Francisco County | 207 | 103 |
| District of Columbia | 247 | 112 |
| Florida | ||
| Broward County | 597 | 349 |
| Duval County | 272 | 164 |
| Hillsborough County | 268 | 197 |
| Miami-Dade County | 1,154 | 598 |
| Orange County | 470 | 273 |
| Palm Beach County | 237 | 152 |
| Pinellas County | 185 | 115 |
| Georgia | ||
| Cobb County | 165 | 63 |
| DeKalb County | 330 | 136 |
| Fulton County | 552 | 308 |
| Gwinnett County | 195 | 71 |
| Illinois | ||
| Cook County | 873 | 343 |
| Indiana | ||
| Marion County | 204 | 103 |
| Louisiana | ||
| East Baton Rouge Parish | 152 | 86 |
| Orleans Parish | 159 | 71 |
| Maryland | ||
| Baltimore City | 201 | 99 |
| Montgomery County | 134 | 56 |
| Prince George’s County | 279 | 128 |
| Massachusetts | ||
| Suffolk County | 135 | 67 |
| Michigan | ||
| Wayne County | 284 | 159 |
| Nevada | ||
| Clark County | 448 | 126 |
| New Jersey | ||
| Essex County | 227 | 101 |
| Hudson County | 147 | 62 |
| New York | ||
| Bronx County | 500 | 181 |
| Kings County | 470 | 264 |
| New York County | 342 | 170 |
| Queens County | 351 | 186 |
| North Carolina | ||
| Mecklenburg County | 267 | 138 |
| Ohio | ||
| Cuyahoga County | 159 | 98 |
| Franklin County | 217 | 123 |
| Hamilton County | 171 | 65 |
| Pennsylvania | ||
| Philadelphia County | 441 | 186 |
| Puerto Rico | ||
| San Juan Municipio | 87 | 41 |
| Tennessee | ||
| Shelby County | 260 | 159 |
| Texas | ||
| Bexar County | 350 | 183 |
| Dallas County | 739 | 407 |
| Harris County | 1,155 | 225 |
| Tarrant County | 305 | 126 |
| Travis County | 178 | 79 |
| Washington | ||
| King County | 248 | 139 |
Abbreviations: CDC, the Centers for Disease Control and Prevention [footnotes only].
Note. Data are based on residence at time of diagnosis of HIV infection. Data are for cases reported to CDC through September 2020, are considered preliminary until a 12-month reporting lag has been reached, and should be interpreted with caution. In addition to being preliminary, data for the year 2020 should be interpreted with caution due to the impact of the COVID-19 pandemic on HIV case surveillance activities in state/local jurisdictions.
| 2019 | |||||
|---|---|---|---|---|---|
| Total diagnoses | ≥1 CD4 or VL tests | No CD4 or VL test | |||
| No. | No. | % | No. | % | |
| Gender | |||||
| Male | 25,539 | 20,836 | 81.6 | 4,703 | 18.4 |
| Female | 6,018 | 4,828 | 80.2 | 1,190 | 19.8 |
| Transgender male-to-femalea | 548 | 450 | 82.1 | 98 | 17.9 |
| Transgender female-to-malea | 37 | 33 | 89.2 | 4 | 10.8 |
| Additional gender identityb | 17 | 15 | 88.2 | 2 | 11.8 |
| Age at diagnosis (yr) | |||||
| 13–24 | 6,702 | 5,307 | 79.2 | 1,395 | 20.8 |
| 25–34 | 11,570 | 9,343 | 80.8 | 2,227 | 19.2 |
| 35–44 | 6,267 | 5,167 | 82.4 | 1,100 | 17.6 |
| 45–54 | 4,295 | 3,570 | 83.1 | 725 | 16.9 |
| ≥55 | 3,325 | 2,775 | 83.5 | 550 | 16.5 |
| Race/ethnicity | |||||
| American Indian/Alaska Native | 163 | 134 | 82.2 | 29 | 17.8 |
| Asian | 663 | 550 | 83.0 | 113 | 17.0 |
| Black/African American | 14,023 | 11,052 | 78.8 | 2,971 | 21.2 |
| Hispanic/Latinoc | 8,563 | 7,202 | 84.1 | 1,361 | 15.9 |
| Native Hawaiian/other Pacific Islander | 62 | 51 | 82.3 | 11 | 17.7 |
| White | 7,878 | 6,509 | 82.6 | 1,369 | 17.4 |
| Multiple races | 807 | 664 | 82.3 | 143 | 17.7 |
| Transmission categoryd | |||||
| Male-to-male sexual contact | 21,431 | 17,601 | 82.1 | 3,830 | 17.9 |
| Injection drug use | |||||
| Male | 1,105 | 843 | 76.3 | 262 | 23.7 |
| Female | 943 | 713 | 75.6 | 230 | 24.4 |
| Male-to-male sexual contact and injection drug use | 1,257 | 1,006 | 80.0 | 251 | 20.0 |
| Heterosexual contacte | |||||
| Male | 2,277 | 1,823 | 80.1 | 454 | 19.9 |
| Female | 5,092 | 4,131 | 81.1 | 961 | 18.9 |
| Totalf | 32,159 | 26,162 | 81.4 | 5,997 | 18.6 |
| 2020 (January – June) | |||||
|---|---|---|---|---|---|
| Total diagnoses | ≥1 CD4 or VL tests | No CD4 or VL test | |||
| No. | No. | % | No. | % | |
| Gender | |||||
| Male | 9,283 | 7,603 | 81.9 | 1,680 | 18.1 |
| Female | 2,198 | 1,796 | 81.7 | 402 | 18.3 |
| Transgender male-to-femalea | 198 | 169 | 85.4 | 29 | 14.6 |
| Transgender female-to-malea | 7 | 7 | 100.0 | 0 | 0.0 |
| Additional gender identityb | 4 | 4 | 100.0 | 0 | 0.0 |
| Age at diagnosis (yr) | |||||
| 13–24 | 2,343 | 1,849 | 78.9 | 494 | 21.1 |
| 25–34 | 4,265 | 3,494 | 81.9 | 771 | 18.1 |
| 35–44 | 2,279 | 1,875 | 82.3 | 404 | 17.7 |
| 45–54 | 1,566 | 1,313 | 83.8 | 253 | 16.2 |
| ≥55 | 1,237 | 1,048 | 84.7 | 189 | 15.3 |
| Race/ethnicity | |||||
| American Indian/Alaska Native | 53 | 44 | 83.0 | 9 | 17.0 |
| Asian | 251 | 218 | 86.9 | 33 | 13.1 |
| Black/African American | 5,310 | 4,257 | 80.2 | 1,053 | 19.8 |
| Hispanic/Latinoc | 2,880 | 2,404 | 83.5 | 476 | 16.5 |
| Native Hawaiian/other Pacific Islander | 24 | 20 | 83.3 | 4 | 16.7 |
| White | 2,954 | 2,453 | 83.0 | 501 | 17.0 |
| Multiple races | 218 | 183 | 83.9 | 35 | 16.1 |
| Transmission categoryd | |||||
| Male-to-male sexual contact | 7,868 | 6,461 | 82.1 | 1,407 | 17.9 |
| Injection drug use | |||||
| Male | 448 | 358 | 79.8 | 90 | 20.2 |
| Female | 334 | 270 | 80.8 | 64 | 19.2 |
| Male-to-male sexual contact and injection drug use | 374 | 306 | 81.9 | 68 | 18.1 |
| Heterosexual contacte | |||||
| Male | 783 | 640 | 81.8 | 142 | 18.2 |
| Female | 1,858 | 1,522 | 81.9 | 337 | 18.1 |
| Totalf | 11,690 | 9,579 | 81.9 | 2,111 | 18.1 |
Abbreviations: CD4, CD4+ T-lymphocyte count (cells/µL) or percentage; VL, viral load (copies/mL). CDC, the Centers for Disease Control and Prevention [footnotes only].
Note. Data are for cases reported to CDC through September 2020, are considered preliminary until a 12-month reporting lag has been reached, and should be interpreted with caution. In addition to being preliminary, data for the year 2020 should be interpreted with caution due to the impact of the COVID-19 pandemic on HIV case surveillance activities in state/local jurisdictions. Linkage to HIV medical care was measured by documentation of ≥1 CD4 or VL tests ≤1 month after HIV diagnosis. Reporting of linkage to HIV medical care data requires a 3-month reporting lag to account for delays in reporting of laboratory results to CDC; therefore, data for the year 2020 on linkage to HIV medical care are for persons with HIV diagnosed during January through June of 2020, that were reported to CDC through June 2020. Data not provided for jurisdictions that do not have laws requiring reporting of all CD4 and viral loads or for areas with incomplete reporting of laboratory data to CDC. Areas without laws: Idaho, New Jersey, and Pennsylvania. Areas with incomplete lab reporting: Arizona, Arkansas, Connecticut, Kansas, Kentucky, Vermont, and Puerto Rico.
aTransgender male-to-female” includes individuals who were assigned “male” sex at birth but have ever identified as “female” gender. “Transgender female-to-male” includes individuals who were assigned “female” sex at birth but have ever identified as “male” gender.
bAdditional gender identity examples include “bigender,” “gender queer,” and “two-spirit.”
cHispanics/Latinos can be of any race.
dData have been statistically adjusted to account for missing transmission category, therefore values may not sum to column subtotals and total. Data presented based on sex at birth and include transgender persons.
eHeterosexual contact with a person known to have, or to be at high risk for, HIV infection.
fIncludes persons whose infection was attributed to hemophilia, blood transfusion, or perinatal exposure or whose risk factor was not reported or not identified. Data not displayed because the numbers were too small to be meaningful.
| 2019 | |||||
|---|---|---|---|---|---|
| Total diagnoses | ≥1 CD4 or VL tests | No CD4 or VL test | |||
| No. | No. | % | No. | % | |
| Alabama | 640 | 507 | 79.2 | 133 | 20.8 |
| Alaska | 27 | 23 | 85.2 | 4 | 14.8 |
| California | 4,230 | 3,493 | 82.6 | 737 | 17.4 |
| Colorado | 460 | 383 | 83.3 | 77 | 16.7 |
| Delaware | 93 | 71 | 76.3 | 22 | 23.7 |
| District of Columbia | 247 | 219 | 88.7 | 28 | 11.3 |
| Florida | 4,402 | 3,680 | 83.6 | 722 | 16.4 |
| Georgia | 2,315 | 1,896 | 81.9 | 419 | 18.1 |
| Hawaii | 65 | 55 | 84.6 | 10 | 15.4 |
| Illinois | 1,238 | 1,027 | 83.0 | 211 | 17.0 |
| Indiana | 485 | 303 | 62.5 | 182 | 37.5 |
| Iowa | 100 | 91 | 91.0 | 9 | 9.0 |
| Louisiana | 887 | 730 | 82.3 | 157 | 17.7 |
| Maine | 30 | 28 | 93.3 | 2 | 6.7 |
| Maryland | 926 | 808 | 87.3 | 118 | 12.7 |
| Massachusetts | 536 | 484 | 90.3 | 52 | 9.7 |
| Michigan | 675 | 568 | 84.1 | 107 | 15.9 |
| Minnesota | 274 | 252 | 92.0 | 22 | 8.0 |
| Mississippi | 477 | 338 | 70.9 | 139 | 29.1 |
| Missouri | 489 | 376 | 76.9 | 113 | 23.1 |
| Montana | 26 | 22 | 84.6 | 4 | 15.4 |
| Nebraska | 81 | 65 | 80.2 | 16 | 19.8 |
| Nevada | 510 | 426 | 83.5 | 84 | 16.5 |
| New Hampshire | 30 | 27 | 90.0 | 3 | 10.0 |
| New Mexico | 147 | 130 | 88.4 | 17 | 11.6 |
| New York | 2,332 | 2,032 | 87.1 | 300 | 12.9 |
| North Carolina | 1,370 | 1,082 | 79.0 | 288 | 21.0 |
| North Dakota | 36 | 33 | 91.7 | 3 | 8.3 |
| Ohio | 975 | 816 | 83.7 | 159 | 16.3 |
| Oklahoma | 309 | 214 | 69.3 | 95 | 30.7 |
| Oregon | 198 | 173 | 87.4 | 25 | 12.6 |
| Rhode Island | 72 | 63 | 87.5 | 9 | 12.5 |
| South Carolina | 688 | 601 | 87.4 | 87 | 12.6 |
| South Dakota | 33 | 26 | 78.8 | 7 | 21.2 |
| Tennessee | 768 | 524 | 68.2 | 244 | 31.8 |
| Texas | 4,176 | 3,102 | 74.3 | 1,074 | 25.7 |
| Utah | 136 | 105 | 77.2 | 31 | 22.8 |
| Virginia | 827 | 650 | 78.6 | 177 | 21.4 |
| Washington | 485 | 433 | 89.3 | 52 | 10.7 |
| West Virginia | 144 | 106 | 73.6 | 38 | 26.4 |
| Wisconsin | 207 | 187 | 90.3 | 20 | 9.7 |
| Wyoming | 13 | 13 | 100 | 0 | 0.0 |
| Total | 32,159 | 26,162 | 81.4 | 5,997 | 18.6 |
| 2020 (January – June) | |||||
|---|---|---|---|---|---|
| Total diagnoses | ≥1 CD4 or VL tests | No CD4 or VL test | |||
| No. | No. | % | No. | % | |
| Alabama | 289 | 232 | 80.3 | 57 | 19.7 |
| Alaska | 16 | 16 | 100.0 | 0 | 0.0 |
| California | 1,420 | 1,221 | 86.0 | 199 | 14.0 |
| Colorado | 135 | 119 | 88.1 | 16 | 11.9 |
| Delaware | 55 | 39 | 70.9 | 16 | 29.1 |
| District of Columbia | 88 | 80 | 90.9 | 8 | 9.1 |
| Florida | 1,802 | 1,520 | 84.4 | 282 | 15.6 |
| Georgia | 796 | 683 | 85.8 | 113 | 14.2 |
| Hawaii | 19 | 17 | 89.5 | 2 | 10.5 |
| Illinois | 374 | 326 | 87.2 | 48 | 12.8 |
| Indiana | 217 | 164 | 75.6 | 53 | 24.4 |
| Iowa | 44 | 40 | 90.9 | 4 | 9.1 |
| Louisiana | 331 | 247 | 74.6 | 84 | 25.4 |
| Maine | 10 | 9 | 90.0 | 1 | 10.0 |
| Maryland | 347 | 322 | 92.8 | 25 | 7.2 |
| Massachusetts | 185 | 157 | 84.9 | 28 | 15.1 |
| Michigan | 241 | 199 | 82.6 | 42 | 17.4 |
| Minnesota | 108 | 93 | 86.1 | 15 | 13.9 |
| Mississippi | 198 | 148 | 74.7 | 50 | 25.3 |
| Missouri | 174 | 135 | 77.6 | 39 | 22.4 |
| Montana | 3 | 2 | 66.7 | 1 | 33.3 |
| Nebraska | 32 | 27 | 84.4 | 5 | 15.6 |
| Nevada | 151 | 121 | 80.1 | 30 | 19.9 |
| New Hampshire | 12 | 11 | 91.7 | 1 | 8.3 |
| New Mexico | 32 | 28 | 87.5 | 4 | 12.5 |
| New York | 894 | 784 | 87.7 | 110 | 12.3 |
| North Carolina | 532 | 441 | 82.9 | 91 | 17.1 |
| North Dakota | 11 | 10 | 90.9 | 1 | 9.1 |
| Ohio | 410 | 366 | 89.3 | 44 | 10.7 |
| Oklahoma | 89 | 55 | 61.8 | 34 | 38.2 |
| Oregon | 77 | 68 | 88.3 | 9 | 11.7 |
| Rhode Island | 20 | 11 | 55.0 | 9 | 45.0 |
| South Carolina | 313 | 281 | 89.8 | 32 | 10.2 |
| South Dakota | 12 | 11 | 91.7 | 1 | 8.3 |
| Tennessee | 323 | 229 | 70.9 | 94 | 29.1 |
| Texas | 1,206 | 769 | 63.8 | 437 | 36.2 |
| Utah | 57 | 27 | 47.4 | 30 | 52.6 |
| Virginia | 306 | 248 | 81.0 | 58 | 19.0 |
| Washington | 206 | 189 | 91.7 | 17 | 8.3 |
| West Virginia | 60 | 47 | 78.3 | 13 | 21.7 |
| Wisconsin | 90 | 83 | 92.2 | 7 | 7.8 |
| Wyoming | 5 | 4 | 80 | 1 | 20.0 |
| Total | 11,690 | 9,579 | 81.9 | 2,111 | 18.1 |
Abbreviations: CD4, CD4+ T -lymphocyte count (cells/µL) or percentage; VL, viral load (copies/mL). CDC, the Centers for Disease Control and Prevention [footnotes only].
“Note. Data are based on residence at diagnosis of HIV infection. Data are for cases reported to CDC through June 2020, are considered preliminary until a 12-month reporting lag has been reached, and should be interpreted with caution. In addition to being preliminary, data for the year 2020 should be interpreted with caution due to the impact of the COVID-19 pandemic on HIV case surveillance activities in state/local jurisdictions.”
Linkage to HIV medical care was measured by documentation of ≥1 CD4 or VL tests ≤1 month after HIV diagnosis. Reporting of linkage to HIV medical care data requires a 3-month reporting lag to account for delays in reporting of laboratory results to CDC; therefore, data for the year 2020 on linkage to HIV medical care are for persons with HIV diagnosed during January through June of 2020, that were reported to CDC through September 2020. Data not provided for jurisdictions that do not have laws requiring reporting of all CD4 and viral loads or for areas with incomplete reporting of laboratory data to CDC. Areas without laws: Idaho, New Jersey, and Pennsylvania. Areas with incomplete lab reporting: Arizona, Arkansas, Connecticut, Kansas, Kentucky, Vermont, and Puerto Rico.
| 2019 | |||||
|---|---|---|---|---|---|
| Total diagnoses | ≥1 CD4 or VL tests | No CD4 or VL test | |||
| No. | No. | % | No. | % | |
| California | |||||
| Alameda County | 220 | 196 | 89.1 | 24 | 10.9 |
| Los Angeles County | 1,447 | 1,160 | 80.2 | 287 | 19.8 |
| Orange County | 246 | 199 | 80.9 | 47 | 19.1 |
| Riverside County | 262 | 211 | 80.5 | 51 | 19.5 |
| Sacramento County | 86 | 77 | 89.5 | 9 | 10.5 |
| San Bernardino County | 271 | 199 | 73.4 | 72 | 26.6 |
| San Diego County | 360 | 311 | 86.4 | 49 | 13.6 |
| San Francisco County | 207 | 199 | 96.1 | 8 | 3.9 |
| District of Columbia | 247 | 219 | 88.7 | 28 | 11.3 |
| Florida | |||||
| Broward County | 597 | 522 | 87.4 | 75 | 12.6 |
| Duval County | 272 | 209 | 76.8 | 63 | 23.2 |
| Hillsborough County | 268 | 230 | 85.8 | 38 | 14.2 |
| Miami-Dade County | 1,154 | 972 | 84.2 | 182 | 15.8 |
| Orange County | 470 | 370 | 78.7 | 100 | 21.3 |
| Palm Beach County | 237 | 187 | 78.9 | 50 | 21.1 |
| Pinellas County | 185 | 158 | 85.4 | 27 | 14.6 |
| Georgia | |||||
| Cobb County | 165 | 144 | 87.3 | 21 | 12.7 |
| DeKalb County | 330 | 271 | 82.1 | 59 | 17.9 |
| Fulton County | 552 | 464 | 84.1 | 88 | 15.9 |
| Gwinnett County | 195 | 162 | 83.1 | 33 | 16.9 |
| Illinois | |||||
| Cook County | 873 | 722 | 82.7 | 151 | 17.3 |
| Indiana | |||||
| Marion County | 204 | 107 | 52.5 | 97 | 47.5 |
| Louisiana | |||||
| East Baton Rouge Parish | 152 | 134 | 88.2 | 18 | 11.8 |
| Orleans Parish | 159 | 131 | 82.4 | 28 | 17.6 |
| Maryland | |||||
| Baltimore City | 201 | 172 | 85.6 | 29 | 14.4 |
| Montgomery County | 134 | 121 | 90.3 | 13 | 9.7 |
| Prince George’s County | 279 | 247 | 88.5 | 32 | 11.5 |
| Massachusetts | |||||
| Suffolk County | 135 | 124 | 91.9 | 11 | 8.1 |
| Michigan | |||||
| Wayne County | 284 | 243 | 85.6 | 41 | 14.4 |
| Nevada | |||||
| Clark County | 448 | 371 | 82.8 | 77 | 17.2 |
| New York | |||||
| Bronx County | 500 | 436 | 87.2 | 64 | 12.8 |
| Kings County | 470 | 400 | 85.1 | 70 | 14.9 |
| New York County | 342 | 303 | 88.6 | 39 | 11.4 |
| Queens County | 351 | 301 | 85.8 | 50 | 14.2 |
| North Carolina | |||||
| Mecklenburg County | 267 | 209 | 78.3 | 58 | 21.7 |
| Ohio | |||||
| Cuyahoga County | 159 | 142 | 89.3 | 17 | 10.7 |
| Franklin County | 217 | 197 | 90.8 | 20 | 9.2 |
| Hamilton County | 171 | 145 | 84.8 | 26 | 15.2 |
| Pennsylvania | |||||
| Philadelphia County | 441 | 374 | 84.8 | 67 | 15.2 |
| Tennessee | |||||
| Shelby County | 260 | 159 | 61.2 | 101 | 38.8 |
| Texas | |||||
| Bexar County | 350 | 249 | 71.1 | 101 | 28.9 |
| Dallas County | 739 | 561 | 75.9 | 178 | 24.1 |
| Harris County | 1,155 | 850 | 73.6 | 305 | 26.4 |
| Tarrant County | 305 | 226 | 74.1 | 79 | 25.9 |
| Travis County | 178 | 153 | 86.0 | 25 | 14.0 |
| Washington | |||||
| King County | 248 | 224 | 90.3 | 24 | 9.7 |
| 2020 (January – June) | |||||
|---|---|---|---|---|---|
| Total diagnoses | ≥1 CD4 or VL tests | No CD4 or VL test | |||
| No. | No. | % | No. | % | |
| California | |||||
| Alameda County | 87 | 72 | 82.8 | 15 | 17.2 |
| Los Angeles County | 506 | 438 | 86.6 | 68 | 13.4 |
| Orange County | 130 | 114 | 87.7 | 16 | 12.3 |
| Riverside County | 96 | 75 | 78.1 | 21 | 21.9 |
| Sacramento County | 6 | 4 | 66.7 | 2 | 33.3 |
| San Bernardino County | 48 | 39 | 81.3 | 9 | 18.8 |
| San Diego County | 75 | 70 | 93.3 | 5 | 6.7 |
| San Francisco County | 74 | 70 | 94.6 | 4 | 5.4 |
| District of Columbia | 88 | 80 | 90.9 | 8 | 9.1 |
| Florida | |||||
| Broward County | 249 | 214 | 85.9 | 35 | 14.1 |
| Duval County | 109 | 90 | 82.6 | 19 | 17.4 |
| Hillsborough County | 139 | 117 | 84.2 | 22 | 15.8 |
| Miami-Dade County | 431 | 361 | 83.8 | 70 | 16.2 |
| Orange County | 191 | 169 | 88.5 | 22 | 11.5 |
| Palm Beach County | 117 | 94 | 80.3 | 23 | 19.7 |
| Pinellas County | 82 | 73 | 89.0 | 9 | 11.0 |
| Georgia | |||||
| Cobb County | 44 | 37 | 84.1 | 7 | 15.9 |
| DeKalb County | 91 | 81 | 89.0 | 10 | 11.0 |
| Fulton County | 227 | 195 | 85.9 | 32 | 14.1 |
| Gwinnett County | 57 | 45 | 78.9 | 12 | 21.1 |
| Illinois | |||||
| Cook County | 284 | 249 | 87.7 | 35 | 12.3 |
| Indiana | |||||
| Marion County | 87 | 67 | 77.0 | 20 | 23.0 |
| Louisiana | |||||
| East Baton Rouge Parish | 63 | 52 | 82.5 | 11 | 17.5 |
| Orleans Parish | 42 | 32 | 76.2 | 10 | 23.8 |
| Maryland | |||||
| Baltimore City | 80 | 72 | 90.0 | 8 | 10.0 |
| Montgomery County | 49 | 47 | 95.9 | 2 | 4.1 |
| Prince George’s County | 98 | 91 | 92.9 | 7 | 7.1 |
| Massachusetts | |||||
| Suffolk County | 57 | 51 | 89.5 | 6 | 10.5 |
| Michigan | |||||
| Wayne County | 107 | 87 | 81.3 | 20 | 18.7 |
| Nevada | |||||
| Clark County | 125 | 98 | 78.4 | 27 | 21.6 |
| New York | |||||
| Bronx County | 144 | 125 | 86.8 | 19 | 13.2 |
| Kings County | 212 | 179 | 84.4 | 33 | 15.6 |
| New York County | 136 | 114 | 83.8 | 22 | 16.2 |
| Queens County | 144 | 132 | 91.7 | 12 | 8.3 |
| North Carolina | |||||
| Mecklenburg County | 90 | 74 | 82.2 | 16 | 17.8 |
| Ohio | |||||
| Cuyahoga County | 82 | 77 | 93.9 | 5 | 6.1 |
| Franklin County | 95 | 84 | 88.4 | 11 | 11.6 |
| Hamilton County | 60 | 55 | 91.7 | 5 | 8.3 |
| Pennsylvania | |||||
| Philadelphia County | 135 | 114 | 84.4 | 21 | 15.6 |
| Tennessee | |||||
| Shelby County | 126 | 80 | 63.5 | 46 | 36.5 |
| Texas | |||||
| Bexar County | 140 | 75 | 53.6 | 65 | 46.4 |
| Dallas County | 302 | 195 | 64.6 | 107 | 35.4 |
| Harris County | 207 | 138 | 66.7 | 69 | 33.3 |
| Tarrant County | 105 | 66 | 62.9 | 39 | 37.1 |
| Travis County | 70 | 43 | 61.4 | 27 | 38.6 |
| Washington | |||||
| King County | 96 | 90 | 93.8 | 6 | 6.3 |
Abbreviations: CD4, CD4+ T -lymphocyte count (cells/µL) or percentage; VL, viral load (copies/mL). CDC, the Centers for Disease Control and Prevention [footnotes only].
“Note. Data are based on residence at diagnosis of HIV infection. Data are for cases reported to CDC through June 2020, are considered preliminary until a 12-month reporting lag has been reached, and should be interpreted with caution. In addition to being preliminary, data for the year 2020 should be interpreted with caution due to the impact of the COVID-19 pandemic on HIV case surveillance activities in state/local jurisdictions.”
Linkage to HIV medical care was measured by documentation of ≥1 CD4 or VL tests ≤1 month after HIV diagnosis. Reporting of linkage to HIV medical care data requires a 3-month reporting lag to account for delays in reporting of laboratory results to CDC; therefore, data for the year 2020 on linkage to HIV medical care are for persons with HIV diagnosed during January through June of 2020, that were reported to CDC through September 2020. Data not provided for jurisdictions that do not have laws requiring reporting of all CD4 and viral loads or for areas with incomplete reporting of laboratory data to CDC. Areas without laws: Idaho, New Jersey, and Pennsylvania. Areas with incomplete lab reporting: Arizona, Arkansas, Connecticut, Kansas, Kentucky, Vermont, and Puerto Rico.
| 2018 | 2019 | 2020 (January – June) | |||||||
|---|---|---|---|---|---|---|---|---|---|
| Persons Prescribed PrEPa | Persons with PrEP Indicationsb | PrEP Coveragec | Persons Prescribed PrEPa | Persons with PrEP Indicationsb | PrEP Coveragec | Persons Prescribed PrEPa | Persons with PrEP Indicationsb | PrEP Coveragec | |
| Area of residence | No. | No. | % | No. | No. | % | No. | No. | % |
| Sex at birth | |||||||||
| Male | 204,863 | 989,200 | 20.7 | 256,873 | 989,200 | 26.0 | 213,871 | 989,200 | 21.6 |
| Female | 15,688 | 227,010 | 6.9 | 21,697 | 227,010 | 9.6 | 15,992 | 227,010 | 7.0 |
| Age (yr) | |||||||||
| 16–24 | 29,413 | 246,290 | 11.9 | 38,033 | 246,290 | 15.4 | 23,998 | 246,290 | 9.7 |
| 25–34 | 90,975 | 434,680 | 20.9 | 114,188 | 434,680 | 26.3 | 90,230 | 434,680 | 20.8 |
| 35–44 | 50,892 | 238,470 | 21.3 | 64,308 | 238,470 | 27.0 | 57,427 | 238,470 | 24.1 |
| 45–54 | 31,602 | 173,420 | 18.2 | 37,529 | 173,420 | 21.6 | 33,282 | 173,420 | 19.2 |
| ≥55 | 17,780 | 123,350 | 14.4 | 24,660 | 123,350 | 20.0 | 25,006 | 123,350 | 20.3 |
| Race/ethnicityd | |||||||||
| Asian/other | 9,510 | 131,180 | 7.2 | 11,698 | 131,180 | 8.9 | 9,399 | 131,180 | 7.2 |
| Black/African American | 28,732 | 468,540 | 6.1 | 37,703 | 468,540 | 8.0 | 30,378 | 468,540 | 6.5 |
| Hispanic/Latino | 33,450 | 312,820 | 10.7 | 42,999 | 312,820 | 13.7 | 35,264 | 312,820 | 11.3 |
| White | 148,971 | 300,650 | 49.5 | 186,318 | 300,650 | 62.0 | 154,901 | 300,650 | 51.5 |
| Total | 220,662 | 1,216,210 | 18.1 | 278,718 | 1,216,210 | 22.9 | 229,943 | 1,216,210 | 18.9 |
Abbreviations: PrEP, preexposure propphylaxis; n/a, not available.
aEstimated using data from IQVIA pharmacy database reported through June 2020 based on an algorithm that included FDA approved drugs for PrEP. Data for which values are unknown were not reported thus values may not sum to column total.
bEstimated using 2018 data from National HIV Surveilance System, National Health and Nutrition Examination Survey, and U.S. Census Bureau’s American Community Survey. Data are rounded to the nearest 10. Data for which values are unknown were not reported thus values may not sum to column total. The data sources used to estimate the number of persons with indications for PrEP have different schedules of data availability. Consequently, the availability of a denominator may lag the availability of a numerator. In this table, 2018 denominators were used for 2018, 2019 and 2020 PrEP coverage data.
cPrEP coverage, reported as a percentage, was calculated as the number who have been prescribed PrEP divided by the estimated number of persons who had indications for PrEP.
dRace/ethnicity data were only available for <40% of persons prescribed PrEP each year. Number prescribed PrEP and PrEP coverage for race/ethnicity reported in the table were adjusted applying the distribution of records with known race/ethnicity to records with missing race/ethnicity.
| 2018 | 2019 | 2020 (January – June) | |||||||
|---|---|---|---|---|---|---|---|---|---|
| Persons Prescribed PrEPa | Persons with PrEP Indicationsb | PrEP Coveragec | Persons Prescribed PrEPa | Persons with PrEP Indicationsb | PrEP Coveragec | Persons Prescribed PrEPa | Persons with PrEP Indicationsb | PrEP Coveragec | |
| Area of residence | No. | No. | % | No. | No. | % | No. | No. | % |
| Alabama | 1,531 | 11,020 | 13.9 | 1,882 | 11,020 | 17.1 | 1,542 | 11,020 | 14.0 |
| Alaska | 196 | 1,780 | 11.0 | 235 | 1,780 | 13.2 | 194 | 1,780 | 10.9 |
| Arizona | 3,531 | 25,780 | 13.7 | 4,654 | 25,780 | 18.1 | 3,944 | 25,780 | 15.3 |
| Arkansas | 610 | 5,130 | 11.9 | 776 | 5,130 | 15.1 | 636 | 5,130 | 12.4 |
| California | 36,360 | 165,030 | 22.0 | 42,775 | 165,030 | 25.9 | 33,998 | 165,030 | 20.6 |
| Colorado | 3,416 | 25,120 | 13.6 | 4,331 | 25,120 | 17.2 | 3,518 | 25,120 | 14.0 |
| Connecticut | 2,315 | 9,560 | 24.2 | 2,768 | 9,560 | 29.0 | 1,959 | 9,560 | 20.5 |
| Delaware | 413 | 4,400 | 9.4 | 477 | 4,400 | 10.8 | 371 | 4,400 | 8.4 |
| District of Columbia | 5,045 | 12,950 | 39.0 | 5,941 | 12,950 | 45.9 | 4,929 | 12,950 | 38.1 |
| Florida | 14,621 | 125,330 | 11.7 | 22,062 | 125,330 | 17.6 | 23,393 | 125,330 | 18.7 |
| Georgia | 6,318 | 39,030 | 16.2 | 8,774 | 39,030 | 22.5 | 7,452 | 39,030 | 19.1 |
| Hawaii | 686 | 4,360 | 15.7 | 848 | 4,360 | 19.4 | 698 | 4,360 | 16.0 |
| Idaho | 368 | 4,790 | 7.7 | 478 | 4,790 | 10.0 | 476 | 4,790 | 9.9 |
| Illinois | 13,935 | 55,860 | 24.9 | 16,788 | 55,860 | 30.1 | 12,801 | 55,860 | 22.9 |
| Indiana | 2,184 | 22,170 | 9.9 | 3,044 | 22,170 | 13.7 | 2,373 | 22,170 | 10.7 |
| Iowa | 1,171 | 4,760 | 24.6 | 1,456 | 4,760 | 30.6 | 1,133 | 4,760 | 23.8 |
| Kansas | 740 | 5,060 | 14.6 | 929 | 5,060 | 18.4 | 699 | 5,060 | 13.8 |
| Kentucky | 1,213 | 12,990 | 9.3 | 1,642 | 12,990 | 12.6 | 1,251 | 12,990 | 9.6 |
| Louisiana | 3,490 | 15,920 | 21.9 | 4,137 | 15,920 | 26.0 | 2,861 | 15,920 | 18.0 |
| Maine | 481 | 3,950 | 12.2 | 648 | 3,950 | 16.4 | 488 | 3,950 | 12.4 |
| Maryland | 3,997 | 27,300 | 14.6 | 5,129 | 27,300 | 18.8 | 3,905 | 27,300 | 14.3 |
| Massachusetts | 8,029 | 24,900 | 32.2 | 10,060 | 24,900 | 40.4 | 8,171 | 24,900 | 32.8 |
| Michigan | 3,511 | 29,570 | 11.9 | 4,541 | 29,570 | 15.4 | 3,610 | 29,570 | 12.2 |
| Minnesota | 3,498 | 21,720 | 16.1 | 4,258 | 21,720 | 19.6 | 3,324 | 21,720 | 15.3 |
| Mississippi | 647 | 4,530 | 14.3 | 949 | 4,530 | 20.9 | 716 | 4,530 | 15.8 |
| Missouri | 2,779 | 18,370 | 15.1 | 3,565 | 18,370 | 19.4 | 2,884 | 18,370 | 15.7 |
| Montana | 183 | 2,290 | 8.0 | 269 | 2,290 | 11.7 | 228 | 2,290 | 10.0 |
| Nebraska | 474 | 2,180 | 21.7 | 630 | 2,180 | 28.9 | 539 | 2,180 | 24.7 |
| Nevada | 1,514 | 11,390 | 13.3 | 2,205 | 11,390 | 19.4 | 1,758 | 11,390 | 15.4 |
| New Hampshire | 506 | 3,020 | 16.8 | 639 | 3,020 | 21.2 | 491 | 3,020 | 16.3 |
| New Jersey | 4,667 | 25,280 | 18.5 | 5,865 | 25,280 | 23.2 | 4,578 | 25,280 | 18.1 |
| New Mexico | 805 | 6,800 | 11.8 | 1,089 | 6,800 | 16.0 | 903 | 6,800 | 13.3 |
| New York | 30,291 | 72,640 | 41.7 | 35,640 | 72,640 | 49.1 | 27,212 | 72,640 | 37.5 |
| North Carolina | 3,981 | 32,490 | 12.3 | 5,486 | 32,490 | 16.9 | 4,625 | 32,490 | 14.2 |
| North Dakota | 164 | 1,520 | 10.8 | 202 | 1,520 | 13.3 | 157 | 1,520 | 10.3 |
| Ohio | 4,793 | 40,320 | 11.9 | 6,259 | 40,320 | 15.5 | 5,182 | 40,320 | 12.9 |
| Oklahoma | 830 | 11,030 | 7.5 | 1,210 | 11,030 | 11.0 | 1,089 | 11,030 | 9.9 |
| Oregon | 2,730 | 19,750 | 13.8 | 3,361 | 19,750 | 17.0 | 2,728 | 19,750 | 13.8 |
| Pennsylvania | 8,652 | 36,490 | 23.7 | 10,399 | 36,490 | 28.5 | 8,361 | 36,490 | 22.9 |
| Puerto Rico | 236 | 9,700 | 2.4 | 336 | 9,700 | 3.5 | 278 | 9,700 | 2.9 |
| Rhode Island | 871 | 3,880 | 22.4 | 1,111 | 3,880 | 28.6 | 907 | 3,880 | 23.4 |
| South Carolina | 1,243 | 10,390 | 12.0 | 1,780 | 10,390 | 17.1 | 1,559 | 10,390 | 15.0 |
| South Dakota | 97 | 910 | 10.7 | 148 | 910 | 16.3 | 105 | 910 | 11.5 |
| Tennessee | 2,614 | 22,460 | 11.6 | 3,949 | 22,460 | 17.6 | 3,678 | 22,460 | 16.4 |
| Texas | 17,672 | 123,790 | 14.3 | 23,490 | 123,790 | 19.0 | 20,464 | 123,790 | 16.5 |
| Utah | 1,485 | 6,840 | 21.7 | 2,008 | 6,840 | 29.4 | 1,758 | 6,840 | 25.7 |
| Vermont | 285 | 1,060 | 26.9 | 343 | 1,060 | 32.4 | 241 | 1,060 | 22.7 |
| Virginia | 3,183 | 31,430 | 10.1 | 4,565 | 31,430 | 14.5 | 3,945 | 31,430 | 12.6 |
| Washington | 8,667 | 40,050 | 21.6 | 10,496 | 40,050 | 26.2 | 9,091 | 40,050 | 22.7 |
| West Virginia | 376 | 5,250 | 7.2 | 600 | 5,250 | 11.4 | 405 | 5,250 | 7.7 |
| Wisconsin | 1,979 | 12,980 | 15.2 | 2,647 | 12,980 | 20.4 | 2,018 | 12,980 | 15.5 |
| Wyoming | 75 | 890 | 8.4 | 93 | 890 | 10.4 | 67 | 890 | 7.5 |
Abbreviations: PrEP, preexposure propphylaxis; n/a, not available.
aEstimated using data from IQVIA pharmacy database reported through June 2020 based on an algorithm that included FDA approved drugs for PrEP. Data for which values are unknown were not reported thus values may not sum to column total.
bEstimated using 2018 data from National HIV Surveilance System, National Health and Nutrition Examination Survey, and U.S. Census Bureau’s American Community Survey. Data are rounded to the nearest 10. Data for which values are unknown were not reported thus values may not sum to column total. The data sources used to estimate the number of persons with indications for PrEP have different schedules of data availability. Consequently, the availability of a denominator may lag the availability of a numerator. In this table, 2018 denominators were used for 2018, 2019 and 2020 PrEP coverage data.
cPrEP coverage, reported as a percentage, was calculated as the number who have been prescribed PrEP divided by the estimated number of persons who had indications for PrEP.
| 2018 | 2019 | 2020 (January – June) | |||||||
|---|---|---|---|---|---|---|---|---|---|
| Persons Prescribed PrEPa | Persons with PrEP Indicationsb | PrEP Coveragec | Persons Prescribed PrEPa | Persons with PrEP Indicationsb | PrEP Coveragec | Persons Prescribed PrEPa | Persons with PrEP Indicationsb | PrEP Coveragec | |
| Area of residence | No. | No. | % | No. | No. | % | No. | No. | % |
| Arizona | |||||||||
| Maricopa County | 2,835 | 22,720 | 12.5 | 3,591 | 22,720 | 15.8 | 3,063 | 22,720 | 13.5 |
| California | |||||||||
| Alameda County | 1,877 | 8,930 | 21.0 | 2,217 | 8,930 | 24.8 | 1,653 | 8,930 | 18.5 |
| Los Angeles County | 12,287 | 67,450 | 18.2 | 14,196 | 67,450 | 21.0 | 11,747 | 67,450 | 17.4 |
| Orange County | 1,628 | 10,510 | 15.5 | 2,114 | 10,510 | 20.1 | 1,737 | 10,510 | 16.5 |
| Riverside County | 1,356 | 11,080 | 12.2 | 1,754 | 11,080 | 15.8 | 1,469 | 11,080 | 13.3 |
| Sacramento County | 790 | 5,920 | 13.3 | 978 | 5,920 | 16.5 | 758 | 5,920 | 12.8 |
| San Bernardino County | 601 | 11,890 | 5.1 | 770 | 11,890 | 6.5 | 589 | 11,890 | 5.0 |
| San Diego County | 3,395 | 14,500 | 23.4 | 3,877 | 14,500 | 26.7 | 3,083 | 14,500 | 21.3 |
| San Francisco County | 7,912 | 10,840 | 73.0 | 8,886 | 10,840 | 82.0 | 6,908 | 10,840 | 63.7 |
| District of Columbia | 5,045 | 12,950 | 39.0 | 5,941 | 12,950 | 45.9 | 4,929 | 12,950 | 38.1 |
| Florida | |||||||||
| Broward County | 2,786 | 20,470 | 13.6 | 3,754 | 20,470 | 18.3 | 4,540 | 20,470 | 22.2 |
| Duval County | 375 | 8,970 | 4.2 | 517 | 8,970 | 5.8 | 504 | 8,970 | 5.6 |
| Hillsborough County | 1,118 | 12,910 | 8.7 | 1,459 | 12,910 | 11.3 | 1,187 | 12,910 | 9.2 |
| Miami-Dade County | 3,824 | 21,760 | 17.6 | 6,607 | 21,760 | 30.4 | 7,290 | 21,760 | 33.5 |
| Orange County | 1,870 | 15,310 | 12.2 | 2,827 | 15,310 | 18.5 | 2,764 | 15,310 | 18.1 |
| Palm Beach County | 576 | 9,170 | 6.3 | 892 | 9,170 | 9.7 | 1,525 | 9,170 | 16.6 |
| Pinellas County | 781 | 9,530 | 8.2 | 1,108 | 9,530 | 11.6 | 897 | 9,530 | 9.4 |
| Georgia | |||||||||
| Cobb County | 383 | 3,070 | 12.5 | 571 | 3,070 | 18.6 | 496 | 3,070 | 16.2 |
| DeKalb County | 1,188 | 6,290 | 18.9 | 1,573 | 6,290 | 25.0 | 1,339 | 6,290 | 21.3 |
| Fulton County | 2,574 | 13,120 | 19.6 | 3,308 | 13,120 | 25.2 | 2,798 | 13,120 | 21.3 |
| Gwinnett County | 455 | 3,240 | 14.0 | 698 | 3,240 | 21.5 | 608 | 3,240 | 18.8 |
| Illinois | |||||||||
| Cook County | 11,471 | 39,060 | 29.4 | 13,682 | 39,060 | 35.0 | 10,452 | 39,060 | 26.8 |
| Indiana | |||||||||
| Marion County | 853 | 9,150 | 9.3 | 1,149 | 9,150 | 12.6 | 906 | 9,150 | 9.9 |
| Louisiana | |||||||||
| East Baton Rouge Parish | 442 | 1,810 | 24.4 | 509 | 1,810 | 28.1 | 394 | 1,810 | 21.8 |
| Orleans Parish | 1,358 | 4,590 | 29.6 | 1,635 | 4,590 | 35.6 | 1,092 | 4,590 | 23.8 |
| Maryland | |||||||||
| Baltimore City | 651 | 6,330 | 10.3 | 918 | 6,330 | 14.5 | 720 | 6,330 | 11.4 |
| Montgomery County | 797 | 5,770 | 13.8 | 961 | 5,770 | 16.7 | 728 | 5,770 | 12.6 |
| Prince George’s County | 645 | 4,040 | 16.0 | 835 | 4,040 | 20.7 | 637 | 4,040 | 15.8 |
| Massachusetts | |||||||||
| Suffolk County | 2,488 | 6,520 | 38.2 | 3,136 | 6,520 | 48.1 | 2,664 | 6,520 | 40.9 |
| Michigan | |||||||||
| Wayne County | 1,035 | 9,270 | 11.2 | 1,289 | 9,270 | 13.9 | 956 | 9,270 | 10.3 |
| Nevada | |||||||||
| Clark County | 1,277 | 11,670 | 10.9 | 1,888 | 11,670 | 16.2 | 1,482 | 11,670 | 12.7 |
| New Jersey | |||||||||
| Essex County | 591 | 4,090 | 14.4 | 708 | 4,090 | 17.3 | 528 | 4,090 | 12.9 |
| Hudson County | 858 | 4,650 | 18.5 | 1,070 | 4,650 | 23.0 | 847 | 4,650 | 18.2 |
| New York | |||||||||
| Bronx County | 2,030 | 5,570 | 36.4 | 2,302 | 5,570 | 41.3 | 1,546 | 5,570 | 27.8 |
| Kings County | 6,278 | 15,650 | 40.1 | 7,503 | 15,650 | 47.9 | 5,705 | 15,650 | 36.5 |
| New York County | 12,276 | 15,540 | 79.0 | 14,172 | 15,540 | 91.2 | 11,199 | 15,540 | 72.1 |
| Queens County | 3,336 | 9,230 | 36.1 | 3,965 | 9,230 | 43.0 | 3,010 | 9,230 | 32.6 |
| North Carolina | |||||||||
| Mecklenburg County | 957 | 8,450 | 11.3 | 1,372 | 8,450 | 16.2 | 1,219 | 8,450 | 14.4 |
| Ohio | |||||||||
| Cuyahoga County | 819 | 7,520 | 10.9 | 988 | 7,520 | 13.1 | 738 | 7,520 | 9.8 |
| Franklin County | 1,622 | 11,620 | 14.0 | 2,060 | 11,620 | 17.7 | 1,794 | 11,620 | 15.4 |
| Hamilton County | 441 | 7,720 | 5.7 | 559 | 7,720 | 7.2 | 462 | 7,720 | 6.0 |
| Pennsylvania | |||||||||
| Philadelphia County | 3,237 | 9,840 | 32.9 | 3,719 | 9,840 | 37.8 | 2,762 | 9,840 | 28.1 |
| Puerto Rico | |||||||||
| San Juan Municipio | − d | 2,190 | n/a | − d | 2,190 | n/a | − d | 2,190 | n/a |
| Tennessee | |||||||||
| Shelby County | 466 | 6,450 | 7.2 | 645 | 6,450 | 10.0 | 598 | 6,450 | 9.3 |
| Texas | |||||||||
| Bexar County | 1,114 | 11,920 | 9.3 | 1,491 | 11,920 | 12.5 | 1,231 | 11,920 | 10.3 |
| Dallas County | 3,251 | 28,670 | 11.3 | 4,221 | 28,670 | 14.7 | 3,852 | 28,670 | 13.4 |
| Harris County | 3,873 | 40,670 | 9.5 | 4,957 | 40,670 | 12.2 | 4,531 | 40,670 | 11.1 |
| Tarrant County | 1,179 | 11,340 | 10.4 | 1,497 | 11,340 | 13.2 | 1,182 | 11,340 | 10.4 |
| Travis County | 3,414 | 11,590 | 29.5 | 4,608 | 11,590 | 39.8 | 3,931 | 11,590 | 33.9 |
| Washington | |||||||||
| King County | 6,112 | 17,890 | 34.2 | 7,373 | 17,890 | 41.2 | 6,515 | 17,890 | 36.4 |
Abbreviations: PrEP, preexposure propphylaxis; n/a, not available.
aEstimated using data from IQVIA pharmacy database reported through June 2020 based on an algorithm that included FDA approved drugs for PrEP. Data for which values are unknown were not reported thus values may not sum to column total.
bEstimated using 2018 data from National HIV Surveilance System, National Health and Nutrition Examination Survey, and U.S. Census Bureau’s American Community Survey. Data are rounded to the nearest 10. Data for which values are unknown were not reported thus values may not sum to column total. The data sources used to estimate the number of persons with indications for PrEP have different schedules of data availability. Consequently, the availability of a denominator may lag the availability of a numerator. In this table, 2018 denominators were used for 2018, 2019 and 2020 PrEP coverage data.
cPrEP coverage, reported as a percentage, was calculated as the number who have been prescribed PrEP divided by the estimated number of persons who had indications for PrEP.
dData value <40 was not reported due to unreliability.