Skip to main content
AIDS Research and Human Retroviruses logoLink to AIDS Research and Human Retroviruses
. 2016 Nov 1;32(10-11):955–963. doi: 10.1089/aid.2015.0345

Increased Antiretroviral Therapy Use and Virologic Suppression in the Bronx in the Context of Multiple HIV Prevention Strategies

David B Hanna 1,, Uriel R Felsen 2, Mindy S Ginsberg 1, Barry S Zingman 2, Robert S Beil 2, Donna C Futterman 3, Howard D Strickler 1, Kathryn Anastos 1,,2
PMCID: PMC5067794  PMID: 26892622

Abstract

Multiple population-based HIV prevention strategies from national, state, local, and institutional levels have been implemented in the Bronx, which has one of the highest HIV prevalences in the U.S. We examined changes in antiretroviral therapy (ART) use and associated outcomes between 2007 and 2014 among patients seen at one of >20 outpatient clinics affiliated with the largest Bronx HIV care provider. Among eligible HIV-infected patients age ≥13 years, we examined annual trends in ART use, mean HIV RNA level, and virologic suppression (<200 copies/ml) overall and among prespecified subgroups. In a subset with suppressed HIV RNA at the end of each year, we determined the percentage whose levels remained suppressed within the next year. Regression models assessed disparities in outcomes. Among 7,196 patients (median age 50, 47% Hispanic, 45% black), we identified consistent increases over time in the percent prescribed ART (78% in 2007 to 93% in 2014) and with virologic suppression (58% to 80%), as mean HIV RNA decreased (351 to 73 copies/ml) (all p < .001). Sustained virologic suppression improved markedly beginning in 2011, coinciding with local test-and-treat initiatives and adoption of expanded treatment guidelines. While disparities among population groups were most pronounced for sustained virologic suppression, those aged 13–24 fared relatively poorly for all outcomes examined (e.g., rate ratio 0.57 for virologic suppression, 95% confidence interval 0.52–0.62, vs. age 65+). Population-wide HIV prevention strategies coincided with improvements in virologic suppression among most population groups. However, more attention is needed to address continued disparities in the HIV care continuum among young people.

Keywords: : antiretroviral therapy, HIV viral load, HIV prevention, test-and-treat, community viral load, young adult

Introduction

For individuals living with HIV infection, achieving and maintaining suppression of HIV RNA levels is the most important goal of antiretroviral therapy (ART), leading to reduced viral replication, slowing or reversal of disease progression, and reduction in transmission.1 The term “community viral load” is a population-based measure of how much virus, measured by HIV RNA levels, is circulating within a community. Community viral load has been proposed to “assess progress in treating HIV-infected persons with antiretroviral medications that would lower the community's viremia,”2 and in turn reduce transmission. Ecologic studies have linked community viral load with the number of new infections in the same area.3,4 “Monitored viral load” is a similar concept to community viral load, but excludes individuals who are not in care or who do not have viral load measurements available. Estimating the true contribution of such individuals to community viral load is challenging since their true number is unknown and their measurements are unavailable, and therefore monitored viral load has been described as a reasonable proxy.2

High prevalence areas may benefit the most from monitoring viral load in a community, particularly in the context of HIV prevention strategies that encourage earlier ART use such as “test-and-treat.”5 The Bronx borough of New York City has one of the largest HIV epidemics in the United States, with an estimated 2% of the 1.4 million Bronx residents reported to be living with HIV.6 Recently, several interventions have been implemented population wide or by individual institutions providing care in the Bronx that could reduce the community's viral load and thus HIV transmission. For example, “The Bronx Knows” was an initiative between 2008 and 2011 by the New York City health department to provide HIV testing to every Bronx resident not previously screened for HIV and link those testing positive to HIV care and services.7 Potential downstream consequences of this program included diagnosis of individuals earlier in the course of infection, earlier treatment, and decreases in community viral load.

Another initiative occurring between 2011 and 2013 was TLC-Plus (HPTN065), a randomized study evaluating the feasibility of a test, linkage-to-care, and treat strategy at participating sites in the Bronx and Washington, DC.8 Other national and local HIV prevention efforts occurring contemporaneously included national treatment guidelines recommending ART initiation at increasingly higher CD4+ counts9; a New York State law mandating HIV testing in health care settings implemented in 201010; and a New York City health department recommendation that ART be offered to all HIV-infected individuals starting in 2011.11

In the context of these multiple HIV prevention strategies, which may facilitate reduced HIV transmission both across and within certain population risk groups, we aimed to assess whether use of ART and related virologic outcomes improved between 2007 and 2014 among HIV-infected individuals in the Bronx. Our objectives were to (1) describe temporal trends in ART use and monitored viral load, as a proxy for community viral load; (2) determine temporal changes in sustained virologic suppression; and (3) identify relative and absolute disparities in these outcomes between population subgroups.

Materials and Methods

Data source

The Einstein/Rockefeller/Hunter CFAR's Clinical Cohort Database (CCDB) contains deidentified data on HIV-infected patients receiving care at hospitals and clinics affiliated with Montefiore Medical Center (MMC), which is the largest provider of HIV care in the Bronx. MMC is an integrated healthcare delivery system with three adult hospitals, a children's hospital, ≥50 ambulatory care sites, and two substance abuse treatment programs (SATPs). Clinics providing HIV primary care include a large infectious disease clinic, an adolescent HIV care clinic, the SATPs, and a network of over 15 general outpatient facilities. Patients in the CCDB are demographically representative with respect to age, sex, race/ethnicity, and HIV transmission risk of the overall HIV-positive population in the Bronx that is described by public health surveillance data.12

The CCDB combines electronic medical information, including inpatient and outpatient records; laboratory test results; prescription data; and intake data from New York State's AIDS Institute Reporting System (AIRS), which records key risk factor information at facilities receiving Ryan White funding. Records are captured through existing electronic systems and combined in a centralized location, where they undergo standardized data checks and are deidentified. This study was approved by the Albert Einstein College of Medicine/Montefiore Medical Center IRB.

Study population

The study population included all HIV-infected persons with at least one encounter in the MMC health system between 2007 and 2014. HIV infection was defined by either a positive HIV Western blot or Multispot; a detectable HIV-1 viral load; or at least three undetectable HIV-1 viral loads ordered concurrently with a CD4+ count. This last criterion captures HIV-infected patients without antibody testing who are well controlled on ART.13

We limited the study to patients with visit records in AIRS (74% of HIV-infected patients) to have systematically collected data on HIV transmission risk, which was one of the characteristics for which we were interested in understanding disparities. This restriction also excluded patients receiving HIV care only through emergency room or inpatient services, or through outpatient clinics not funded by the Ryan White Program. Additional inclusion criteria included age ≥13 years and at least one HIV-1 viral load recorded during the period.

Variables of interest

We assessed three outcomes during each calendar year: ART use, monitored viral load, and sustained virologic suppression. We defined ART use as having at least one ART prescription recorded. Monitored viral load was assessed in multiple ways providing complementary information on viremia, based on guidance developed by the CDC2: first, as the average of the last recorded HIV-1 viral load in each year for all eligible patients; second, as the total monitored viral load, based on the sum of each patient's last recorded viral load in each year; third, as the percent of patients whose last recorded viral load was suppressed, defined as <200 copies/ml.9 Viral load was assessed by Versant HIV-1 RNA 3.0 (bDNA), used until 2010, or Abbott Real-Time HIV Viral Load, introduced in 2010.

Virologic suppression assessed at a single point in time does not capture whether suppression is maintained over time. We determined “sustained virologic suppression” among the subset of patients whose last viral load in each year was suppressed and who had at least one additional viral load recorded over the next 366 days. We calculated the time from initial suppression to virologic rebound (≥200 copies/ml).14 If rebound did not occur within 366 days, the patient was censored. Sustained virologic suppression is represented by the Kaplan–Meier estimate of the percent of suppressed individuals who did not experience virologic rebound within 1 year.

Other variables examined included sex, age (13–24, 25–44, 45–64, 65+ years), race/ethnicity (non-Hispanic black, Hispanic, non-Hispanic white, other/unknown), and insurance status (public, private, self-pay). HIV transmission risk factor was categorized as men who have sex with men (MSM), injection drug use (IDU) history, perinatal, and heterosexual contact or other risk. Nine percent of both male and female patients did not report an HIV risk factor; these patients were also categorized as heterosexual/other risk.

Statistical methods

To examine time trends in ART use, monitored viral load, and sustained virologic suppression, we reported annual percentages, means, or Kaplan–Meier estimates. For mean viral load, we used the geometric mean to reduce the influence of outlying measurements.2 We tested trends using Poisson regression, except for the time-to-event sustained virologic suppression outcome, for which we used Cox regression.

To assess disparities in ART use and virologic suppression over the study period by patient characteristics, we developed Poisson regression models that included sex, age, race/ethnicity, transmission risk, insurance status, and calendar year. Because patients could contribute data to each year of the study, we used generalized estimating equations with an independent correlation structure to account for clustering by individuals. We did not institute a variable selection strategy owing to the limited number of covariates included. We determined differences in time trends by population groups with time × covariate interaction terms. We used Cox regression to assess disparities in sustained virologic suppression, with a frailty term to account for multiple observations per patient. Models for sustained virologic suppression included the same covariates as those for ART use and monitored viral load.

We performed sensitivity analyses to examine whether disparities in the youngest age group were affected by transmission category or by expanding the age group to age 29. When possible, we also performed sensitivity analyses that included patients not in the AIRS system. Analyses used SAS 9.3 and R 3.0.2.

Results

There were 7,196 HIV-infected individuals between 2007 and 2014 who met inclusion criteria, with 31,052 eligible person-years of data, reported from over 20 general and specialty outpatient clinics across the Bronx (Table 1).

Table 1.

Characteristics of HIV-Infected Outpatients in the Einstein/Rockefeller/Hunter Center for AIDS Research's Clinical Cohort Database, 2007–2014 (N = 7,196)

Characteristics N %
Sex
 Male 4,113 57
 Female 3,083 43
Agea (median years, IQR) 50 42–57
 13–24 years 266 4
 25–44 years 1,945 27
 45–64 years 4,413 61
 65+ years 572 8
Race/ethnicity
 Hispanic 3,373 47
 Black, non-Hispanic 3,216 45
 White, non-Hispanic 296 4
 Other or unknown 311 4
Transmission risk, among men
 MSM 1,306 32
 IDU history 774 19
 Heterosexual, other, or unknown 1,957 48
 Perinatal 76 2
Transmission risk, among women
 Transgender women 32 1
 Injection drug use history 371 12
 Heterosexual, other, or unknown 2,570 83
 Perinatal 110 4
Insurance statusa
 Public 6,439 89
 Private 602 8
 Self-paid 155 2
CD4+ counta (median cells/μl, IQR) (N = 7,161) 450 232–695
 <200 cells/μl 1,541 22
 200–349 cells/μl 1,198 17
 350–499 cells/μl 1,231 17
 500+ cells/μl 3,192 45
a

At most recent visit.

IDU, injection drug use; IQR, interquartile range; MSM, men who have sex with men.

Females comprised 43% of the population. Median age at the end of the study period was 50 years, and median CD4+ count was 450 cells/μL. Most patients were either Hispanic (of any race) (47%) or non-Hispanic black (45%). The vast majority (89%) of patients were publicly insured. Individuals reporting either heterosexual/other risk comprised 48% of men, with additional 32% of men reporting sex with men, 19% a history of IDU, and 1% perinatal transmission. Among women, 12% reported a history of IDU, 2% perinatal transmission, and the remainder heterosexual/other risk. Among those aged 13–24, 44% were MSM, 31% reported perinatal transmission, and the remainder heterosexual/other risk.

Trends and disparities in ART use and monitored viral load

Figure 1 shows calendar-year trends in ART use and monitored viral load. The percent of patients with at least one ART prescription increased from 78% in 2007 to 93% in 2014 (ptrend < .001). The mean viral load decreased during the time period, from 351 copies/ml in 2007 to 73 copies/ml in 2014, while the percent of patients with a suppressed viral load (<200 copies/ml) increased from 58% to 80% (each ptrend < .001). Increases in ART use and virologic suppression were observed across all population subgroups defined by age, sex, race/ethnicity, transmission risk factor, and insurance status (Supplementary Figs. 1–5; Supplementary Data are available online at www.liebertpub.com/aid). Significant changes over time for these measures were observed by age (p < .001).

FIG. 1.

FIG. 1.

Use of antiretroviral therapy and monitored viral load measures among HIV-infected outpatient clinical population, 2007–2014.

Table 2 shows the percent of patients with at least one ART prescription and with suppressed viral load, as well as mean and total monitored viral load in different population groups. Groups with the highest percentage of ART use had consequently the highest percentage with virologic suppression and lowest mean viral load.

Table 2.

ART Use and Monitored Viral Load Measures by Patient Characteristics, 2007–2014

  ART use Monitored viral load measures
Characteristics Total person-years Percent (%) with at least one ART prescriptiona Adjusted RR for ART prescription (95% CI) p Mean viral loadb(copies/ml) (SD) Total monitored viral load (× 1 million copies)c Percent (%) with suppressed viral loada Adjusted RR for suppressed viral load (95% CI) p
Calendar year (per year)   1.02 (1.02, 1.03) <.001 1.04 (1.04, 1.05) <.001
 2007 3,354 78 1.00 Ref. 351 (16) 32.3 58 1.00 Ref.
 2008 3,544 80 1.03 (1.02, 1.05) .002 275 (15) 28.1 61 1.06 (1.03, 1.09) <.001
 2009 3,835 83 1.07 (1.05, 1.09) <.001 229 (13) 26.3 65 1.10 (1.07, 1.13) <.001
 2010 3,890 88 1.13 (1.11, 1.15) <.001 191 (21) 39.5 64 1.08 (1.05, 1.12) <.001
 2011 3,963 90 1.15 (1.13, 1.17) <.001 140 (18) 32.8 69 1.16 (1.12, 1.19) <.001
 2012 4,111 91 1.17 (1.15, 1.19) <.001 86 (13) 22.3 76 1.26 (1.22, 1.30) <.001
 2013 4,178 93 1.18 (1.16, 1.21) <.001 82 (13) 24.2 78 1.29 (1.25, 1.33) <.001
 2014 4,177 93 1.18 (1.16, 1.21) <.001 73 (11) 20.9 80 1.31 (1.27, 1.35) <.001
Sex
 Male 16,713 88 1.00 Ref. 155 (17) 16.8 69 1.00 Ref.
 Female 14,334 87 0.97 (0.96, 0.99) .0002 139 (14) 11.6 70 1.01 (0.99, 1.04) .27
Age
 13–24 years 1,703 65 0.70 (0.66, 0.75) <.001 497 (20) 2.4 48 0.57 (0.52, 0.62) <.001
 25–44 years 9,795 85 0.97 (0.94, 0.999) .04 240 (19) 11.8 62 0.76 (0.72, 0.79) <.001
 45–64 years 17,968 91 1.02 (0.99, 1.05) .17 109 (13) 13.4 75 0.91 (0.88, 0.94) <.001
 65+ years 1,581 90 1.00 Ref. 62 (9) 0.7 83 1.00 Ref.
Race/ethnicity
 Black, non-Hispanic 13,396 86 0.90 (0.74, 1.10) .31 166 (17) 13.1 68 1.13 (0.84, 1.51) .42
 Hispanic 15,370 89 0.88 (0.77, 1.01) .08 137 (15) 13.1 71 0.89 (0.91, 1.02) .22
 White, non-Hispanic 1,196 86 1.00 Ref. 129 (16) 1.2 74 1.00 Ref.
 Other race/ethnicity 1,085 88 0.90 (0.78, 1.03) .12 118 (14) 0.9 74 0.92 (0.76, 1.12) .41
Transmission risk
 IDU history 5,103 89 0.99 (0.97, 1.01) .36 142 (15) 4.4 70 0.97 (0.93, 1.00) .05
 MSM 5,297 85 0.99 (0.97, 1.01) .26 165 (17) 5.4 68 1.04 (1.01, 1.08) .02
 Perinatal 849 82 1.17 (1.11, 1.24) <.001 303 (20) 1.1 57 1.11 (0.999, 1.23) .05
 Heterosexual risk or other 19,803 88 1.00 Ref. 140 (15) 17.4 70 1.00 Ref.
Insurance status
 Public 27,769 88 1.00 Ref. 149 (16) 25.6 69 1.00 Ref.
 Private 2,717 83 0.94 (0.92, 0.97) <.001 114 (13) 1.9 74 1.08 (1.04, 1.12) <.001
 Self-paid 561 70 0.83 (0.78, 0.88) <.001 343 (21) 0.8 57 0.88 (0.81, 0.95) .002

Suppressed viral load defined as <200 copies/ml. Rate ratios adjusted for all other variables in table.

a

Percent of all person-years.

b

Geometric mean.

c

Annualized total viral load multiplied by 1,000,000, except for calendar year-specific estimates.

ART, antiretroviral therapy; CI, confidence interval; RR, rate ratio; SD, standard deviation.

Among those with the least amount of ART use and virologic suppression were those aged 13–24 and those with perinatal transmission. When examining the 13–24 age group, only those with perinatal transmission had higher ART use than the MSM or heterosexual groups that approached levels of the older age groups toward the end of the time frame (Supplementary Fig. 6a). However, virologic suppression was low among the 13–24 age group regardless of the mode of transmission (Supplementary Fig. 6b). Sensitivity analyses that also included HIV+ patients seen exclusively in emergency room or inpatient settings, or non-Ryan White-funded outpatient settings, resulted in slightly lower percentages of ART use and virologic suppression (Supplementary Table S1).

In multivariable analyses, disparities by age in ART use and virologic suppression persisted. However, for some factors, differences in the association with ART use versus virologic suppression were observed. For example, women were less likely to be prescribed ART compared with men (rate ratio [RR] 0.97, 95% confidence interval [CI] 0.96–0.99), but virologic suppression was similar by sex. Those infected perinatally were more likely to be prescribed ART than those with heterosexual transmission (RR 1.17, 95% CI 1.11–1.24), whereas the association with virologic suppression was not statistically significant.

Population groups with greater total monitored viral load differed from those with greater mean viral load in a few respects, due to differences in underlying population size and HIV prevalence. While the youngest individuals had the highest mean viral load, those aged 25–44 and 45–64 had a higher annual total monitored viral load (11.8 and 13.4 million copies, respectively), due to a greater number of individuals in each of these groups. By transmission risk, heterosexual individuals had one of the lowest mean viral loads, but the highest total monitored viral load. MSM represented an increasing proportion of the total monitored viral load in the Bronx in more recent years, surpassing IDU in 2010 (Supplementary Fig. 7).

Trends and disparities in sustained virologic suppression

There were 4,681 individuals (16,381 person-years) eligible for analysis of sustained virologic suppression. Figure 2 shows Kaplan–Meier curves of sustained virologic suppression across successive cohorts of virologically suppressed patients over the study period. For most of the period, the percent of patients with sustained virologic suppression over 1 year was ∼80%, increasing by 2012 to about 85%.

FIG. 2.

FIG. 2.

Sustained virologic suppression among HIV-infected outpatient population, by year of suppression, 2007–2013.

Table 3 shows differences in sustained virologic suppression by population group. Many observed disparities were in the same direction as those of initial virologic suppression, but more pronounced. For example, the age gradient observed for sustained virologic suppression was greater, with the youngest patients (age 13–24) more than twice as likely to not sustain virologic suppression as those 65 or older (hazard ratio [HR] 2.53, 95% CI 1.67–3.82), controlling for sex, race/ethnicity, transmission category, insurance status, and year. The association was similar in a sensitivity analysis that excluded perinatally infected patients (HR 2.70, 95% CI 1.75–4.14). Both black and Hispanic patients were significantly less likely to sustain virologic suppression compared with white patients. While there were relatively few disparities by transmission risk in adjusted analyses for ART and virologic suppression, IDU were significantly less likely to sustain suppression compared to those with heterosexual risk.

Table 3.

Association with Sustained Virologic Suppression After 1 Year, 2007–2013 (N = 4,681)

Characteristics Estimated % with sustained virologic suppressiona Estimated % with virologic rebound within 1 year Adjusted HR for time to virologic rebound (95% CI) p
Overall 82 18    
Calendar year (per year)
 2007 80 20 1.00 Ref.
 2008 79 21 1.09 (0.94, 1.28) .24
 2009 77 23 1.31 (1.13, 1.52) <.001
 2010 81 19 1.18 (1.01, 1.38) .04
 2011 84 16 0.93 (0.79, 1.09) .36
 2012 85 15 0.69 (0.59, 0.81) <.001
 2013 86 14 0.65 (0.55, 0.76) <.001
Sex
 Male 82 18 1.00 Ref.
 Female 82 18 0.97 (0.84, 1.12) .72
Age
 13–24 years 74 26 2.53 (1.67, 3.82) <.001
 25–44 years 78 22 1.85 (1.36, 2.53) <.001
 45–64 years 84 16 1.25 (0.92, 1.68) .15
 65+ years 89 11 1.00 Ref.
Race/ethnicity
 Black, non-Hispanic 82 18 1.49 (1.11, 2.00) .008
 Hispanic 82 18 1.42 (1.06, 1.90) .02
 White, non-Hispanic 87 13 1.00 Ref.
 Other race/ethnicity 92 8 0.47 (0.24, 0.90) .02
Transmission risk
 IDU history 79 21 1.31 (1.10, 1.57) .003
 MSM 84 16 0.81 (0.66, 0.99) .04
 Perinatal 75 25 0.93 (0.60, 1.46) .76
 Heterosexual risk or other 83 17 1.00 Ref.
Insurance status
 Public 82 18 1.00 Ref.
 Private 87 13 0.65 (0.53, 0.79) <.001
 Self-paid 83 17 0.88 (0.60, 1.28) .51

HRs adjusted for all other variables in table.

a

Based on Kaplan–Meier estimate.

CI, confidence interval; HR, hazard ratio; IDU, injection drug use; MSM, men who have sex with men.

Discussion

During a time when multiple changes to HIV screening and treatment practices occurred in the Bronx, we identified a consistent increase in ART use in our HIV population, with a concurrent increase in virologic suppression and decrease in the overall monitored viral load. We observed improvements across most population subgroups, including those traditionally believed to be less engaged in care such as IDU, but adolescents and young adults had the worst results for all outcomes. In contrast to the consistent increases in ART use and virologic suppression, the proportion of patients with sustained virologic suppression increased only in more recent years, after 2010. This improvement seemed most prominent when “test-and-treat” strategies and more aggressive treatment guidelines were being implemented.

Our observations extend findings of earlier U.S. studies reporting greater ART use and virologic suppression over time,15–17 linked, in part, to improved risk profiles of available ART drugs and regimens with fewer pills or dosings.18,19 Our study is unique in that it addresses the poorest urban county in the U.S.,20 one that is disproportionately affected by HIV,6 yet home to multiple recent initiatives intended to improve HIV care continuum outcomes,21 including those focused on the early initiation of ART.8–11 It is especially encouraging that with recent calls by the White House to increase the number of HIV-infected people receiving ART to ≥90% and viral suppression to ≥80%,22 despite persistent socioeconomic disparities in the Bronx, our patient population is at or very close to these targets. In a broader context, because early initiation of ART has now been adopted as a central tenet of the global response to HIV,23 our study provides early insight into the potential impact that such “test-and-treat” strategies may have in real-world scenarios.

We observed an improvement in sustained virologic suppression that occurred only after 2010, in contrast to consistent improvements over the entire period in overall virologic suppression. This suggests that there had been a steady core of patients for whom efforts at maintaining virologic suppression after initial success were unsuccessful in earlier years, but that this group is diminishing, potentially due to more recent improvements in ease of treatment regimens, adherence levels, or more consistent messaging on the importance of maintaining suppression by providers. While other studies have shown mixed results in sustained virologic suppression over time,24–28 the gains we observed are encouraging. Continued monitoring would be useful to ensure durability of individual and public health benefits of ART, as recommended in the National HIV/AIDS Strategy for the United States.22

Assessing community viral load by specific risk characteristics may be informative in understanding how within-group and between-group transmission may be affected by prevention initiatives. We confirmed known disparities in young people: less than half of patients aged 13–24 were virologically suppressed and over one-quarter could not sustain suppression for 1 year, despite the existence in our network of an adolescent medical clinic specifically devoted to their care. These findings were observed regardless of mode of transmission and are consistent with recent U.S. studies reporting suboptimal virologic suppression29,30 and retention in care in this age group.31

While the prescribing of ART in the past may have been delayed among those in the early stages of HIV who were not expected to be adherent to complicated regimens, our study shows that ART use in youth has increased more recently, likely due to the availability of more tolerable regimens. Nonetheless, inadequate virologic suppression as a whole suggests that targeted programs are needed among youth who encourage care retention and emphasize the value of consistent ART use to maintain health and reduce the risk of transmission to others.29 Developmental barriers (e.g., incomplete brain development, fear of disclosure, lack of family support as a result of stigma or homophobia) may require more intensive adherence support and interventions addressing contextual barriers to ongoing care (e.g., housing, transportation, job security) within this group.

As a contrast, older HIV-infected adults were more likely to be prescribed ART and sustain virologic suppression; yet, the sheer number of older individuals in our HIV+ population relative to younger individuals resulted in a larger disparity in the total viral load potentially circulating in the community (e.g., 13.4 million copies in those aged 45–64 vs. 2.4 million copies among those aged 13–24). For “test-and-treat” initiatives to be successful within transmission networks that often cross demographic categories, including age,32 emphasis on viral suppression among groups with low individual viral loads, but high total viral loads, may be important.

We found that ART use was slightly, but significantly lower in women than men overall, by 3% in adjusted analyses. However, examining ART use by sex over time showed that this disparity rapidly disappeared over the course of the study. This is consistent with a report from a similar urban clinical cohort in Baltimore showing diminishing disparities in ART use by sex between 1997 and 2010.17 Our finding that virologic suppression by sex was similar despite this small difference in ART use is notable, given mixed findings in the literature regarding sex differences in ART adherence and HIV clinical outcomes.33,34 While our findings hold promise that sex in itself may contribute less to health disparities than in the past, continued assessment of its role in HIV clinical outcomes is warranted given known sex differences in pathogenesis that are independent of health care access.35

Race/ethnicity did not appear to impede ART use, suggesting that our system may not have the same barriers to prescribing ART with respect to racial and ethnic minorities as has been observed in other settings.36 We acknowledge, however, that a limited number of white patients in our population may limit our ability to fully support this claim. Indeed, black race (vs. white race) as well as public insurance were negatively associated with sustained virologic suppression, potentially reflecting underlying differences in health care access or socioeconomic background that persist despite availability of ART. Neither access to health care nor socioeconomic status beyond insurance status is systematically assessed in our database.

While some studies have found that differences in HIV outcomes by race/ethnicity and insurance status are attenuated or disappear when controlling for socioeconomic factors,37,38 other studies have found these differences to persist despite confounder control.39–41 Similarly, IDU, a group traditionally believed to be less engaged in care, were able to achieve virologic suppression at levels similar to other risk groups, but sustaining virologic response remained more difficult for them as well. In summary, a further understanding of the factors contributing to sustained virologic suppression is warranted.

This analysis illustrates the translation of evidence-based recommendations to real-world clinical practice. Because multiple overlapping initiatives occurred simultaneously in the Bronx, we could not easily evaluate the effectiveness of individual programs, but were nonetheless able to observe contemporaneous improvements in key treatment outcomes. Our cohort is unique in that it includes a high proportion of women (>40%) and measures care in an area with HIV prevalence consistent with a generalized epidemic. We used indicators established to evaluate prevention, treatment, and care services,42–44 and thus our findings can be compared with other jurisdictions. Prescription data provided face validity that changes in viral load were due at least, in part, to increased ART use, and go beyond what most public health surveillance systems contain.

Our study has some limitations. First, we do not capture individuals not receiving care in our network or episodes of care among our cohort occurring outside of our system, and we do not account for those who are infected, but not diagnosed with HIV. We also excluded patients receiving care through emergency room or inpatient services or those not seen at Ryan White-funded outpatient clinics. Therefore, our use of monitored viral load in this study as a proxy for community viral load may result in estimates of virologic suppression that are higher than the true value in the underlying population, if individuals not in active care have unsuppressed RNA levels.45 This is supported by our sensitivity analyses that show slightly worse outcomes when relaxing our exclusion criteria. Nonetheless, our institution is the largest HIV care provider in the Bronx, and our population has been shown to be similar to the overall Bronx HIV-positive population,12 suggesting that the monitored viral load that we report may be generalizable to the entire borough.

Another limitation is that a change in viral load assays used institutionally occurred in 2010, resulting in slight discontinuities in time trends that year. This is an unavoidable consequence of using real-world clinical data. We partially accounted for this by calculating the geometric mean viral load, which reduces measurement variability. Finally, our findings may not apply to other areas.

Conclusion

In summary, we demonstrated improvements in several ART outcomes over time in one of the poorest U.S. communities, broadly correlating with the implementation of multiple population-based HIV prevention strategies. Continued emphasis should be placed on efforts to improve maintenance of virologic suppression, such as those improving treatment adherence and retention in care, across all population groups. Adolescents and young adults may need additional efforts once in HIV care to overcome barriers that impede virologic suppression, as the implications of life-long treatment with ART are most salient for this age group.

Supplementary Material

Supplemental data
Supp_Figs1-5.pdf (474KB, pdf)
Supplemental data
Supp_Fig6.pdf (104.8KB, pdf)
Supplemental data
Supp_Table1.pdf (20.3KB, pdf)
Supplemental data
Supp_Fig7.pdf (74.6KB, pdf)

Acknowledgments

We thank Benjamin W. Tsoi, MD, MPH and Sarah L. Braunstein, PhD of the New York City Department of Health and Mental Hygiene for their input on HIV prevention efforts occurring in the city. This work was supported by the Einstein/Rockefeller/Hunter Center for AIDS Research (P30-AI-051519) and the Harold and Muriel Block Institute for Clinical and Translational Research at Einstein and Montefiore (UL1-TR-001073).

Author Disclosure Statement

D.C.F. has received both clinical trial and unrestricted educational grants from Gilead. K.A. reports advisory board membership within the last 3 years for Bristol-Myers Squibb. The remaining authors declare that they have no competing interests.

References

  • 1.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 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Centers for Disease Control and Prevention. Guidance on community viral load: A family of measures, definitions, and method for calculation. Available at www.ct.gov/dph/lib/dph/aids_and_chronic/surveillance/statewide/community_viralload_guidance.pdf, accessed July30, 2013
  • 3.Wood E, Kerr T, Marshall BD, et al. : Longitudinal community plasma HIV-1 RNA concentrations and incidence of HIV-1 among injecting drug users: Prospective cohort study. BMJ 2009;338:b1649. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Das M, Chu PL, Santos GM, et al. : Decreases in community viral load are accompanied by reductions in new HIV infections in San Francisco. PLoS One 2010;5:e11068. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Cohen MS, Gay CL: Treatment to prevent transmission of HIV-1. Clin Infect Dis 2010;50 Suppl 3:S85–S95 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.New York City Department of Health and Mental Hygiene. HIV/AIDS Annual Surveillance Statistics. Available at www.nyc.gov/html/doh/html/data/hivtables.shtml, accessed July30, 2014
  • 7.Myers JE, Braunstein SL, Shepard CW, et al. : Assessing the impact of a community-wide HIV testing scale-up initiative in a major urban epidemic. J Acquir Immune Defic Syndr 2012;61:23–31 [DOI] [PubMed] [Google Scholar]
  • 8.Donnell DJ, Hall HI, Gamble T, et al. : Use of HIV case surveillance system to design and evaluate site-randomized interventions in an HIV prevention study: HPTN 065. Open AIDS J 2012;6:122–130 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.U.S. Dept. of Health and Human Services. Archived adult and adolescent guidelines. Available at http://aidsinfo.nih.gov/guidelines/archive/adult-and-adolescent-guidelines, accessed April4, 2013
  • 10.New York State Department of Health. Chapter 308 of the Laws of 2010, HIV Testing Law, Mandated Report. Available at www.health.ny.gov/diseases/aids/testing/law/docs/chapter_308.pdf, accessed April4, 2013
  • 11.Farley T: DOHMH now recommends offering antiretroviral treatment to any person living with HIV, regardless of the person's CD4 cell count. Available at www.nyc.gov/html/doh/downloads/pdf/ah/nyc-hivart-letter.pdf, accessed April4, 2013
  • 12.Felsen UR, Hanna DB, Ginsberg MS, et al. : The Einstein-Montefiore Center for AIDS Research HIV Integrated Clinical Database: Cohort development and description [abstract]. Paper presented at New York City Epidemiology Forum, New York, NY, 2014 [Google Scholar]
  • 13.Felsen UR, Bellin EY: Cunningham CO and Zingman BS. Development of an electronic medical record-based algorithm to identify patients with unknown HIV status. AIDS Care 2014;26:1318–1325 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Cambiano V, Lampe FC, Rodger AJ, et al. : Use of a prescription-based measure of antiretroviral therapy adherence to predict viral rebound in HIV-infected individuals with viral suppression. HIV Med 2010;11:216–224 [DOI] [PubMed] [Google Scholar]
  • 15.Althoff KN, Buchacz K, Hall HI, et al. : U.S. trends in antiretroviral therapy use, HIV RNA plasma viral loads, and CD4 T-lymphocyte cell counts among HIV-infected persons, 2000 to 2008. Ann Intern Med 2012;157:325–335 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Dombrowski JC, Kitahata MM, Van Rompaey SE, et al. : High levels of antiretroviral use and viral suppression among persons in HIV care in the United States, 2010. J Acquir Immune Defic Syndr 2013;63:299–306 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Moore RD, Keruly JC, Bartlett JG: Improvement in the health of HIV-infected persons in care: Reducing disparities. Clin Infect Dis 2012;55:1242–1251 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Slama L, Li X, Brown T, et al. : Increases in duration of first highly active antiretroviral therapy over time (1996–2009) and associated factors in the Multicenter AIDS Cohort Study. J Acquir Immune Defic Syndr 2014;65:57–64 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Hanna DB, Hessol NA, Golub ET, et al. : Increase in single-tablet regimen use and associated improvements in adherence-related outcomes in HIV-infected women. J Acquir Immune Defic Syndr 2014;65:587–596 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Roberts S: One in five New York City residents living in poverty. Available at www.nytimes.com/2011/09/22/nyregion/one-in-five-new-york-city-residents-living-in-poverty.html, accessed August31, 2015
  • 21.Gardner EM, McLees MP, Steiner JF, et al. : The spectrum of engagement in HIV care and its relevance to test-and-treat strategies for prevention of HIV infection. Clin Infect Dis 2011;52:793–800 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.White House Office of National AIDS Policy. National HIV/AIDS Strategy for the United States: Updated to 2020. Available at https://aids.gov/federal-resources/national-hiv-aids-strategy/nhas-update.pdf, accessed August4, 2015
  • 23.World Health Organization. Guideline on When to Start Antiretroviral Therapy and on Pre-Exposure Prophylaxis for HIV. Geneva: World Health Organization, 2015 [PubMed] [Google Scholar]
  • 24.Mocroft A, Ruiz L, Reiss P, et al. : Virological rebound after suppression on highly active antiretroviral therapy. AIDS 2003;17:1741–1751 [DOI] [PubMed] [Google Scholar]
  • 25.Smith CJ, Phillips AN, Dauer B, et al. : Factors associated with viral rebound among highly treatment-experienced HIV-positive patients who have achieved viral suppression. HIV Med 2009;10:19–27 [DOI] [PubMed] [Google Scholar]
  • 26.Raboud J, Blitz S, Walmsley S, et al. : Effect of gender and calendar year on time to and duration of virologic suppression among antiretroviral-naive HIV-infected individuals initiating combination antiretroviral therapy. HIV Clin Trials 2010;11:340–350 [DOI] [PubMed] [Google Scholar]
  • 27.Yehia BR, Fleishman JA, Metlay JP, et al. : Sustained viral suppression in HIV-infected patients receiving antiretroviral therapy. JAMA 2012;308:339–342 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Torian LV, Xia Q: Achievement and maintenance of viral suppression in persons newly diagnosed with HIV, New York City, 2006–2009: Using population surveillance data to measure the treatment part of ‘test and treat’. J Acquir Immune Defic Syndr 2013;63:379–386 [DOI] [PubMed] [Google Scholar]
  • 29.Zanoni BC, Mayer KH: The adolescent and young adult HIV cascade of care in the United States: Exaggerated health disparities. AIDS Patient Care STDS 2014;28:128–135 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Yehia BR, Rebeiro P, Althoff KN, et al. : Impact of age on retention in care and viral suppression. J Acquir Immune Defic Syndr 2015;68:413–419 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Torian LV, Xia Q, Wiewel EW: Retention in care and viral suppression among persons living with HIV/AIDS in New York City, 2006–2010. Am J Public Health 2014;104:e24–e29 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Beck EC, Birkett M, Armbruster B, Mustanski B: A Data-driven simulation of HIV spread among young men who have sex with men: Role of age and race mixing and STIs. J Acquir Immune Defic Syndr 2015;70:186–194 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Puskas CM, Forrest JI, Parashar S, et al. : Women and vulnerability to HAART non-adherence: A literature review of treatment adherence by gender from 2000 to 2011. Curr HIV/AIDS Rep 2011;8:277–287 [DOI] [PubMed] [Google Scholar]
  • 34.Castilho JL, Melekhin VV, Sterling TR: Sex differences in HIV outcomes in the highly active antiretroviral therapy era: A systematic review. AIDS Res Hum Retroviruses 2014;30:446–456 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Addo MM, Altfeld M: Sex-based differences in HIV type 1 pathogenesis. J Infect Dis 2014;209 Suppl 3:S86–S92 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Fleishman JA, Yehia BR, Moore RD, et al. : Disparities in receipt of antiretroviral therapy among HIV-infected adults (2002–2008). Med Care 2012;50:419–427 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Anastos K, Schneider MF, Gange SJ, et al. The association of race, sociodemographic, and behavioral characteristics with response to highly active antiretroviral therapy in women. J Acquir Immune Defic Syndr 2005;39:537–544 [PubMed] [Google Scholar]
  • 38.Silverberg MJ, Leyden W, Quesenberry CP, Jr, Horberg MA. Race/ethnicity and risk of AIDS and death among HIV-infected patients with access to care. J Gen Intern Med 2009;24:1065–1072 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Palella FJ, Jr, Baker RK, Buchacz K, et al. : Increased mortality among publicly insured participants in the HIV Outpatient Study despite HAART treatment. AIDS 2011;25:1865–1876 [DOI] [PubMed] [Google Scholar]
  • 40.Murphy K, Hoover DR, Shi Q, et al. : Association of self-reported race with AIDS death in continuous HAART users in a cohort of HIV-infected women in the United States. AIDS 2013;27:2413–2423 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Schneider G, Juday T, Wentworth C III, et al. : Impact of health care payer type on HIV stage of illness at time of initiation of antiretroviral therapy in the USA. AIDS Care 2013;25:1470–1476 [DOI] [PubMed] [Google Scholar]
  • 42.Committee to Review Data Systems for Monitoring HIV Care and Institute of Medicine. Monitoring HIV Care in the United States: Indicators and Data Systems. Washington, DC: Natl Academies Press, 2012 [PubMed] [Google Scholar]
  • 43.Horberg MA, Aberg JA, Cheever LW, et al. : Development of national and multiagency HIV care quality measures. Clin Infect Dis 2010;51:732–738 [DOI] [PubMed] [Google Scholar]
  • 44.Forsyth A, Yakovchenko V: Secretary Sebelius approves indicators for monitoring HHS-funded HIV services. Available at http://blog.aids.gov/2012/08/secretary-sebelius-approves-indicators-for-monitoring-hhs-funded-hiv-services.html, accessed March22, 2013
  • 45.Xia Q, Wiewel EW, Torian LV. Revisiting the methodology of measuring HIV community viral load. J Acquir Immune Defic Syndr 2013;63:e82–e84 [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplemental data
Supp_Figs1-5.pdf (474KB, pdf)
Supplemental data
Supp_Fig6.pdf (104.8KB, pdf)
Supplemental data
Supp_Table1.pdf (20.3KB, pdf)
Supplemental data
Supp_Fig7.pdf (74.6KB, pdf)

Articles from AIDS Research and Human Retroviruses are provided here courtesy of Mary Ann Liebert, Inc.

RESOURCES