The burden of HIV infection varies widely across the United States.1 To advance the prevention goals of the National HIV/AIDS Strategy (NHAS) updated to 2020 and to maximize the effectiveness of HIV prevention methods, the Centers for Disease Control and Prevention (CDC) pursues a High Impact Prevention approach to direct efforts to communities where HIV is most heavily concentrated.2,3 Achieving national HIV prevention goals requires actively using data to monitor and assess progress and then refining and improving prevention programs as needed in the context of each state. Methods that allow for timely and economical estimation of HIV incidence, prevalence, and undiagnosed infection can be beneficial to inform national and local efforts for improving the effectiveness of existing HIV prevention and care programs.
Data reported to the CDC's National HIV Surveillance System are used to monitor progress toward reaching NHAS 2020 goals. The methods on which previously published estimates of HIV incidence and prevalence from the National HIV Surveillance System were based had significant limitations. National incidence estimates relied on the use of an assay to determine the recency of infection and were based on data from a limited number of areas extrapolated to the United States.4–8 Because HIV reporting was implemented over time by different jurisdictions, prevalence estimation required statistical adjustments to account for incomplete reporting of historical cases.9 Approaches were needed for estimating HIV incidence and prevalence that would be minimally affected by changes in testing technologies and incomplete case data, while being able to provide reliable assessments of trends over time.
New methods using the first CD4 value after HIV diagnosis to measure the progression of HIV disease can readily be applied to HIV surveillance data to produce national and state-level estimates of HIV incidence, prevalence, and undiagnosed infection.10 As HIV disease progresses, the CD4 cell count can be used to estimate the time since infection at the date of CD4 test, assuming no treatment has been received. The National HIV Surveillance System incorporates into routine case surveillance the reporting of the first CD4 value after diagnosis of HIV infection and most jurisdictions collect all CD4 values.11 These data, in combination with the prevalence of diagnosed infection and data on deaths among persons with HIV, can be used to generate annual estimates of the number of new HIV infections (incidence, diagnosed, and undiagnosed), HIV prevalence (diagnosed and undiagnosed), and the percentage of persons with undiagnosed infection.
In this article, we applied the method developed by Song et al10 to estimate the distribution of delay from infection to diagnosis based on a well-characterized CD4 depletion model and produced national and state-level estimates of HIV incidence, prevalence, and the percentage undiagnosed during 2010–2014.
We first estimated the date of HIV infection for each person with a CD4 test using a CD4 depletion model.10 All persons with diagnosed HIV did not have a CD4 test. Persons with CD4 tests were assigned a weight to account for those without a CD4 test based on the year of HIV diagnosis, sex, race/ethnicity, transmission category, age at diagnosis, and the status at the end of the study period—whether the person living with HIV whose disease had never been classified as AIDS, died without ever having been classified as AIDS, or had progressed to AIDS regardless of whether living or dead. Because we report results for persons aged 13 or older, if a person has an estimated date of infection before age 13, then the date of infection for this person is set to the date when the person reaches the age of 13. The distribution of diagnosis delay (from HIV infection to diagnosis) was then estimated and used to estimate annual HIV incidence, which represents persons with diagnosed and undiagnosed infection. HIV prevalence, which represents counts of persons with diagnosed and undiagnosed HIV infections who were alive at the end of a given year, was estimated by subtracting cumulative deaths from cumulative infections. The number of persons with undiagnosed HIV infection was estimated by subtracting cumulative diagnoses from cumulative infections. The proportion of undiagnosed infection was estimated by dividing the number undiagnosed by the total HIV prevalence for each year. To reflect model uncertainty, all estimates were rounded to the nearest 100 for estimates of more than 1000 and to the nearest 10 for estimates of less than 1000. Estimated annual percentage changes (EAPCs) were calculated for each outcome and considered statistically significant when the Student t test P-value was <0.05. Data from individual states were deemed sufficient to produce numerically stable estimates if they had ≥100 diagnoses for each year of the analysis. Regions were defined based on the U.S. Census Bureau designations.15 Cases were assigned to each state based on the most recent address known to CDC at the end of 2014.
In the United States, 207,120 persons received a diagnosis of HIV infection during 2010–2014 and were reported to the National HIV Surveillance System by June 2016. Thirty-five states and the District of Columbia had ≥100 diagnoses each year during 2010–2014, allowing for the calculation of numerically stable estimates.
The estimated annual number of HIV infections (incidence) decreased 10.3% in the United States during 2010–2014 from 41,900 to 37,600 (EAPC = −3.1%) (Table 1; see Supplemental Digital Content for annual estimates for the United States and by jurisdiction, http://links.lww.com/QAI/B61). HIV incidence significantly decreased in Georgia (EAPC = −6.2%), New York (EAPC = −5.0%), and the district of Columbia (EAPC = −10.9). HIV incidence remained stable in 33 states.
In 2014, HIV incidence ranged from 110 in Delaware to 5100 in California with 5 states (California, Georgia, Florida, New York, and Texas) accounting for 51.6% of new infections in the United States. By region, the South accounted for the highest percentage of infections in 2014 (50%), followed by the West (21%), Northeast (18%), and Midwest (11%).
During 2010–2014, HIV prevalence increased 9.1% in the United States from 1,015,600 to 1,107,700 (EAPC = 2.2%) (Table 2; see Supplemental Digital Content for annual estimates for the United States and by jurisdiction, http://links.lww.com/QAI/B61). HIV prevalence increased in 4 states [California, Florida, Georgia, and Texas (EAPC range 1.2%–3.3%)]. HIV prevalence remained stable in 32 jurisdictions.
In 2014, HIV prevalence ranged from 3000 persons in Utah to 145,900 in New York. Five states (California, Florida, Georgia, New York, and Texas) accounted for 50% of all persons living with HIV in the United States (Table 2). By region, the South (45%) accounted for the highest percentage of persons living with HIV, followed by the Northeast (24%), West (19%), and Midwest (12%).
Undiagnosed HIV Infection
During 2010–2014, the number of persons with undiagnosed infection in the United States decreased from an estimated 174,000 to 166,000; the percentage undiagnosed decreased from 17.1% to 15.0% (EAPC = −3.3%) (Table 3; see Supplemental Digital Content for annual estimates for the United States and by jurisdiction, http://links.lww.com/QAI/B61). The percentage of undiagnosed HIV infections decreased in Georgia (EAPC = −6.2%) and Texas (EAPC = −4.0%). Percentages of undiagnosed infection remained stable in 34 jurisdictions.
In 2014, percentages of persons living with undiagnosed HIV infection ranged from 9.9% (3600 persons) in Pennsylvania to 19.2% (18,300) in Texas (Table 3). Five states (California, Georgia, Florida, New York, and Texas) accounted for 51% of undiagnosed infections in the United States. By region, persons residing in the South (50%) accounted for the highest percentage of persons with undiagnosed infection, followed by the Northeast (19%), West (19%), and Midwest (12%).
HIV incidence has declined in the United States since the implementation of the National HIV/AIDS Strategy in 2010, a signal that collective prevention and treatment efforts at federal, state and local levels are having an impact. Three states had significant declines in annual infections (Georgia, New York, and the District of Columbia) and 2 states (Georgia and Texas) had significant declines in undiagnosed infections indicating that more work is needed in HIV prevention at the jurisdiction level. Five states (California, Georgia, Florida, New York, and Texas) accounted for approximately half of all new HIV infections, all persons living with HIV infection, and all persons with undiagnosed infection in the United States by the end of 2014. Disparities were also seen among persons residing in the south, which account for 35% of the U.S. population, but for nearly half of each measured outcome.
Using the results from this analysis, the national HIV transmission [T(x)] can be calculated as the estimated incidence of HIV infection [I(x)] divided by the estimated prevalence of HIV infection [P(x)], multiplied by 100, or T(x) = [I(x)/P(x)] × 100.16 The annual HIV transmission rate for the United States decreased during 2010–2014 from 4.13 to 3.39 and clearly shows progress in HIV prevention. As the number of persons living with HIV increases, the potential for transmission increases as well; however, national declines in annual infections point to prevention successes. Declines in HIV incidence may be due to decreases in numbers of persons with undiagnosed infection and increases in numbers of persons receiving care and treatment.17 Increases in HIV prevalence are likely because of improvements in HIV treatment resulting in longer survival. Studies have shown that, in addition to improving the health of people living with HIV, early treatment with antiretroviral medications dramatically reduces their risk of transmitting the virus to others.18,19 Retention in HIV medical care and viral suppression has increased nationally over time, although outcomes vary by jurisdiction.20 Primary prevention, such as condom use and uptake of preexposure prophylaxis, or PrEP, are also effective in reducing infections, although PrEP use has only recently increased and may not yet be reflected in the results.21–24 Decreases in undiagnosed HIV infection might be attributable to intensified testing efforts, and evidence suggests that the percentage of persons ever tested for HIV infection has increased, especially among men who have sex with men, the group with the highest HIV prevalence.
The use of the CD4 method to estimate HIV incidence, prevalence, and undiagnosed infection is made possible by improvements in HIV case surveillance which allow for the use of data that are readily available for all states. Past methods relied on partial data from selected states and cities or historical data from early years of the epidemic, when reporting was less complete. Because of changes in methods, earlier estimates of diagnosed prevalence and overall prevalence are higher than the estimates in this report. The earlier model included adjustments for incomplete reporting of cases in the early years of the epidemic. The CD4-based method does not rely on historical adjustments for incomplete reporting; it relies on the more complete, timely reporting of data to CDC in recent years.
The findings in this report are subject to several limitations. In addition to the possible violation of assumptions required by the CD4 model (eg, the CD4 depletion model is correct, diagnosis delay was not significantly changed in recent years, etc.),10 there are 2 major limitations. First, state-level estimates were produced based on the assumption that a person's infection, diagnosis, and death all occurred in the same jurisdiction. The underlying assumption is that inmigration and outmigration are nearly equal for each jurisdiction. To get the most accurate estimates, the most recent known address reported to the surveillance system by year-end 2014 was used to identify cases in each state. So delays or errors in address reporting, or imbalanced inmigration and outmigration could affect jurisdictional estimates. Second, state-level estimates were based on models using HIV surveillance data reported from all jurisdictions in the United States. It is possible that estimates presented for a state may be less variable from year to year and may be biased toward the national average compared to estimates produced using state-level models. Finally, some jurisdictional estimates are uncertain as illustrated by their wide confidence intervals. Caution should be used when interpreting these estimates, and conclusions about trends should be based on EAPCs for multiple years rather than single-year estimates.
Jurisdictional progress in HIV prevention must be accelerated. In 2014, 1 jurisdiction (Pennsylvania) met the NHAS 2020 objective to increase the percentage of persons living with HIV who know their serostatus to ≥90%, a critical component of the strategy to meet the goal of reducing new HIV infections in the United States.2 Additional efforts are needed to ensure that all jurisdictions meet the goals of the national strategy. Persons with undiagnosed infection contribute to nearly one-third of ongoing transmissions.25 Because the percentage of undiagnosed HIV varies by state, efforts tailored to each state's unique circumstances might be needed to increase the percentage of persons aware of their infection. Continued efforts to implement routine HIV screening in health care settings and focus on targeted testing to populations in states with disproportionately high HIV burden, including the 5 states (California, Georgia, Florida, New York, and Texas) with the highest numbers of new and undiagnosed infections and southern states, might help further reduce undiagnosed HIV infection. Prompt treatment after HIV diagnosis is recommended for all persons with HIV.26 Linkage to HIV medical care varies across jurisdictions and progress is needed to improve viral suppression among persons living with diagnosed HIV from the currently estimated 55% to the national goal of 80%.2,20 Action taken at the federal, state, and local level should ensure that persons living with HIV have access to care and treatment, to achieve viral suppression, to improve their health, and to reduce transmission. Having routine and reliable estimates of HIV incidence, prevalence, and undiagnosed infection are important to implementing and evaluating prevention interventions as jurisdictions can use these estimates to determine the effectiveness of interventions in reducing incidence. Annual updates to these estimates will allow for monitoring progress toward reaching the national benchmark for the percentage of persons with HIV who are aware of their status and ultimately reducing HIV incidence.
1. Centers for Disease Control and Prevention. State HIV
Prevention Progress Report, 2010–2013. Available at: http://www.cdc.gov
-stateprogressreport.pdf. Published December, 2015. Accessed June 6, 2017.
2. The White House Office of National AIDS Policy. National HIV
/AIDS Strategy for the United States: Updated to 2020. 2015. Available at: https://http://www.hiv.gov
/sites/default/files/nhas-update.pdf. Accessed June 6, 2017.
3. Centers for Disease Control and Prevention. High-Impact HIV
Prevention: CDC's Approach to Reducing HIV
Infections in the United States. Available at: https://http://www.cdc.gov
/pdf/policies_NHPC_Booklet.pdf. Accessed June 6, 2017.
4. Karon JM, Song R, Kaplan E, et al. Estimating HIV incidence
in the United States from HIV
data and biomarker HIV
test results. Stat Med. 2008;27:4617–4633.
5. Hall HI, Song R, Rhodes P, et al. Estimation of HIV incidence
in the United States. JAMA. 2008;300:520–529.
6. Prejean J, Song R, Hernandez A, et al. Estimated HIV incidence
in the United States, 2006–2009. PLoS One. 2011;6:e17502.
7. Centers for Disease Control and Prevention. Estimated HIV incidence
in the United States, 2007–2010. HIV
Surveill Suppl Rep. 2012;17. Available at: http://http://www.cdc.gov
/resources/reports/#supplemental. Published December, 2012. Accessed June 6, 2017.
8. An Q, Kang J, Song R, Hall HI. A Bayesian hierarchical model with novel prior specifications for estimating HIV
testing rates. Stat Med. 2016;35:1471–1487.
9. Hall HI, An Q, Tang T, et al. Prevalence
of diagnosed and undiagnosed HIV
infection—United States, 2008–2012. MMWR Morb Mortal Wkly Rep. 2015;64:657–662.
10. Song R, Hall IH, Green TA, et al. Using CD4
data to estimate HIV incidence
, and percent of undiagnosed
infections in the United States. J Acquir Immune Defic Syndr. 2017;74:3–9.
11. Cohen SM, Gray KM, Ocfemia MC, et al. The status of the national HIV surveillance
system, United States, 2013. Public Health Rep. 2014;129:335–341.
12. Lodi S, Phillips A, Touloumi G, et al, on behalf of the CASCADE Collaboration in EuroCoorda. Time from human immunodeficiency virus seroconversion to reaching CD4
+ cell count thresholds, <200, <350, and <500 Cells/mm3: assessment of need following changes in treatment guidelines. HIV
13. Touloumi G, Pantazis N, Pillay D, et al, on behalf of the CASCADE collaboration in EuroCoord. Impact of HIV
-1 subtype on CD4
count at HIV
seroconversion, rate of decline, and viral load set point in European seroconverter cohorts. Clin Infect Dis. 2013;56:888–897.
14. Hall HI, Song R, Szwarcwald CL, et al. Time from infection with the human immunodeficiency virus to diagnosis, United States. J AIDS. 2015;69:248–251.
15. U.S. Census Bureau. Census Bureau Regions and Divisions with State FIPS Codes. Available at: http://www2.census.gov/geo/pdfs/maps-data/maps/reference/us_regdiv.pdf. Accessed June 6, 2017.
16. Holtgrave DR, Hall HI, Prejean J. HIV
transmission rates in the United States, 2006–2008. Open AIDS J. 2012;6:26–28.
17. Bradley H, Hall HI, Wolitski RJ, et al. Vital signs: HIV
diagnosis, care, and treatment among persons living with HIV
—United States, 2011. MMWR Morb Mortal Wkly Rep. 2014;63:1113–1117.
18. Cohen MS, Chen YQ, McCauley M, et al. Prevention of HIV
-1 infection with early antiretroviral therapy. N Engl J Med. 2011;365:493–505.
19. Hall HI, Tang T, Johnson AS, et al. Timing of linkage to care after HIV
diagnosis and time to viral suppression. J Acquir Immune Defic Syndr. 2016;72:e57–e60.
20. Centers for Disease Control and Prevention. Monitoring selected national HIV
prevention and care objectives by using HIV surveillance
data—United States and 6 dependent areas, 2014. HIV
Surveill Supplemental Rep. 2016;21. Available at: http://http://www.cdc.gov
/. Published July, 2016. Accessed June 6, 2017.
21. Smith DK, Van Handel M, Wolitski RJ, et al. Vital Signs: estimated percentages and numbers of adults with Indications for preexposure prophylaxis to prevent HIV
Acquisition—United States, 2015. MMWR Morb Mortal Wkly Rep. 2015;64:1291–1295.
22. US Public Health Service. Preexposure prophylaxis for HIV
prevention in the United States—2013: a clinical practice guideline. Available at: https://http://www.cdc.gov
/pdf/prepguidelines2014.pdf. Accessed March 1, 2017.
23. Laufer F, O'Connel MA, Feldman I, et al. Vital Signs: increased Medicaid prescriptions for preexposure prophylaxis against HIV
infection—New York, 2012–2015. MMWR Morb Mortal Wkly Rep. 2016;64:1296–1301. Available at: https://www.cdc.gov/mmwr/preview/mmwrhtml/mm6446a5.htm. Accessed March 1, 2017.
24. Volk JE, Marcus JL, Phengrasamy T, et al. No new HIV
infections with increasing use of HIV
preexposure prophylaxis in a clinical practice setting. Clin Infect Dis. 2015;61:1601–1603.
25. Skarbinski J, Rosenburg E, Paz-Bailey G, et al. Human Immunodeficiency virus transmission at each step of the care continuum in the United States. JAMA Intern Med. 2015;175:588–596.
26. Panel on Antiretroviral Guidelines for Adults and Adolescents. Guidelines for the use of antiretroviral agents in HIV
-1–infected adults and adolescents. Available at: http://go.usa.gov/vdGA. Updated July 14, 2016. Accessed June 6, 2017.
CD4; HIV; incidence; prevalence; surveillance; undiagnosed; state-level
Supplemental Digital Content
Copyright © 2017 Wolters Kluwer Health, Inc. All rights reserved.