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. Author manuscript; available in PMC: 2022 Sep 1.
Published in final edited form as: AIDS Care. 2020 Sep 27;33(9):1146–1154. doi: 10.1080/09540121.2020.1826396

HIV-positive persons who inject drugs experience poor health outcomes and unmet needs for care services

Sharoda Dasgupta 1, Yunfeng Tie 1, Ansley Lemons-Lyn 1, Dita Broz 1, Kate Buchacz 1, R Luke Shouse 1
PMCID: PMC8628508  NIHMSID: NIHMS1752223  PMID: 32985227

Abstract

Comparison of social determinants of health and clinical outcomes between HIV-positive persons who inject drugs (PWID) and HIV-positive persons who do not inject drugs is essential to understanding disparities and informing HIV prevention and care efforts; however, nationally representative estimates are lacking. Interview and medical record data were collected for the Medical Monitoring Project during 2015–2018 among U.S. adults with diagnosed HIV. Among HIV-positive PWID (N=340) and HIV-positive persons who do not inject drugs (N=11,475), we reported weighted percentages and prevalence ratios with predicted marginal means to compare differences between groups (P<.05). Associations with clinical outcomes were adjusted for age, race/ethnicity, and gender. HIV-positive PWID were more likely to be homeless (29.1% vs. 8.1%) and incarcerated (18.3% vs. 4.9%). HIV-positive PWID were less likely to be retained in HIV care (aPR: 0.85 [95% CI: 0.77–0.94]), and were more likely to have poor HIV outcomes, have unmet needs for care services (aPR: 1.50 [1.39–1.61]), seek non-routine care, and experience healthcare discrimination (aPR: 1.42 [1.17–1.73]). Strengthening interventions supporting (1) continuity of care given high levels of incarceration and housing instability, (2) early ART initiation and adherence support, and (3) drug treatment and harm reduction programs to limit transmission risk may improve outcomes among HIV-positive PWID.

Keywords: Injection drug use, social determinants of health, transmission risk

Introduction

During 2017, 9% of diagnosed HIV infections in the U.S. were attributed to injection drug use or male-to-male sexual contact and injection drug use (CDC). Persons who inject drugs (PWID) may be at risk for HIV infection through injection equipment sharing (e.g., syringes) and certain sexual behaviors, such as condomless sex. Starting in late 2014, a large outbreak of HIV infection occurred among PWID in Scott County, Indiana, which heralded increases in HIV transmission risk among PWID that have been documented in outbreaks in other areas of the U.S. over the last 5 years, including Washington and Massachusetts (Cranston et al., 2019; Golden et al., 2019; Peters et al., 2016).

The “Ending the HIV Epidemic” initiative highlights the need to prevent new HIV transmission and treat people with HIV rapidly and effectively, particularly among vulnerable populations, such as PWID. In the context of the national opioid crisis, meeting these goals among PWID may be particularly challenging. The number of PWID has been increasing over time (Zibbell et al., 2018), and compared with other persons, HIV-positive PWID experience poorer clinical outcomes, such as antiretroviral therapy (ART) initiation and sustained viral suppression, and higher mortality rates (CDC; Crepaz et al., 2016; Lewden et al., 2007; Lucas et al., 2001; Mehta et al., 2010; Palepu et al., 2003; Westergaard et al., 2012). PWID are more likely to experience social determinants of poor health, including high levels of unstable housing, incarceration, and poverty, which may be interrelated and also, in turn, could affect substance use patterns (Nandi et al., 2010; Strathdee et al., 1997). These social determinants of health could also contribute to poorer access to healthcare services (Adler & Newman, 2002; Bradford et al., 2007), and thus, suboptimal clinical outcomes and increased HIV transmission risk for persons with HIV (Bradford et al., 2007; Cohen et al., 2016; Colasanti et al., 2017; Mugavero et al., 2012). In addition, PWID are disproportionately affected by comorbidities, such as hepatitis C, skin abscesses, and endocarditis, which can complicate HIV care management, and thus, lead to adverse HIV clinical outcomes (Altice et al., 2010; Kamarulzaman & Altice, 2015; Zibbell et al., 2018).

People with HIV who inject drugs may experience unique challenges in accessing care and healthcare outcomes compared with HIV-positive persons who do not inject drugs. Comparison of social determinants of health and HIV outcomes between HIV-positive PWID and HIV-positive persons who do not inject drugs is an essential step towards understanding and addressing disparities that HIV-positive PWID experience, and informing HIV prevention and care efforts supporting the “Ending the HIV Epidemic” initiative. In addition, comparison of clinical outcomes that could directly affect HIV outcomes, such as depression, use of non-routine care, and unmet needs for substance use, may provide additional insight into how to address disparities between HIV-positive PWID and HIV-positive persons who do not inject drugs. Although some studies have been conducted to understand differences in experiences related to HIV care engagement and clinical outcomes among HIV-positive PWID and HIV-positive persons who do not inject drugs, these studies are often limited in scope (i.e., focus on a particular geographic area), have limited sample size, or are outdated (Lucas et al., 2001; Mehta et al., 2010; Palepu et al., 2003). Further, examining social determinants of health and clinical outcomes together provides a more complete picture of the challenges that HIV-positive may face related to HIV care engagement, antiretroviral treatment (ART) adherence, and viral suppression. Having up-to-date, representative benchmark estimates of these characteristics may be helpful in informing interventions to improve outcomes among HIV-positive PWID at a national level. We used nationally representative data from the Medical Monitoring Project (MMP) to describe and compare selected characteristics, including social determinants of health and clinical outcomes, among U.S. HIV-positive PWID and HIV-positive persons who do not inject drugs.

Methods

Population

MMP is an annual, cross-sectional survey designed to produce nationally representative estimates of behavioral and clinical characteristics among adults with diagnosed HIV in the United States. During the 2015, 2016, and 2017 MMP cycles, MMP used a two-stage sampling design. First, 16 states and 1 territory were sampled from all states in the U.S., the District of Columbia, and Puerto Rico. Jurisdictions were selected using a probability proportional to size sampling strategy based on AIDS prevalence at the end of 2002, such that areas with higher prevalence had a higher probability of selection. Next, a simple random sample of persons aged ≥18 years with diagnosed HIV was sampled annually within each selected jurisdiction from the National HIV Surveillance System (NHSS), a census of persons with diagnosed HIV in the U.S. Data on demographic, behavioral, and clinical characteristics were collected through face-to-face or phone interviews conducted by trained interviewers within individual MMP areas. Medical records were abstracted for interviewed participants who received HIV care during the previous two years. MMP is conducted as a part of routine surveillance and is considered non-research. Participating jurisdictions obtained institutional review board approval for data collection as needed and informed consent was obtained from all participants.

All sampled jurisdictions participated in MMP, including California (including the separately funded jurisdictions of Los Angeles County and San Francisco), Delaware, Florida, Georgia, Illinois (including Chicago), Indiana, Michigan, Mississippi, New Jersey, New York (including New York City), North Carolina, Oregon, Pennsylvania (including Philadelphia), Puerto Rico, Texas (including Houston), Virginia, and Washington. Data were collected from June to May for the 2015, 2016, and 2017 cycle years; response rates for jurisdictions was 100% and for sampled persons ranged from 40%–46%.

Measures: injection drug use and social determinants of health

Interviewers collected information about self-reported injection drug use; those who injected drugs in the past 12 months were considered to be people who inject drugs. Data on social determinants of health and demographic characteristics, including age, gender, race/ethnicity, household poverty threshold according to the Department of Health and Human Services poverty guidelines (DHHS, 2015; 2016; 2014), healthcare coverage, incarceration, and homelessness were also collected through participant interviews. Healthcare coverage was categorized as any private; public only, excluding Ryan White HIV/AIDS Program (RWHAP) / AIDS Drug Assistance Program (ADAP) only but including Medicare and Medicaid; and RWHAP/ADAP only or no coverage.

Measures: HIV outcomes

The three primary HIV care continuum outcomes included retention care, antiretroviral therapy (ART) adherence, and sustained viral suppression. For this analysis, persons with two or more elements of outpatient HIV care at least 90 days apart during the previous 12 months were considered to be retained in HIV care. Outpatient HIV care included self-reported information or medical record documentation of a visit with a healthcare provider, or medical record documentation of a viral load or CD4 test result, HIV drug resistance test, ART prescription, Pneumocystis jiroveci (PCP) prophylaxis, or Mycobacterium avium complex (MAC) prophylaxis. Persons who reported needing but not receiving at least one care service (e.g., HIV care management, ART adherence support, drug/alcohol treatment) were considered to have an unmet need (CDC, 2019). ART use and dose adherence based on the past 30 days were combined into a single variable with the following categories: not currently taking ART, currently taking ART but not 100% adherent, currently taking ART and 100% adherent.

Viral loads and CD4 cell counts (CD4 counts) were abstracted from medical records. Persons for whom all documented viral load measurements in the past 12 months were undetectable or <200 copies/mL were considered to have sustained viral suppression. The most recent CD4 count was categorized as <200, 200–349, 350–499, and ≥500 cells/mm3. All information collected was based on the past 12 months unless otherwise indicated.

Measures: clinical outcomes that may affect HIV care continuum

In addition to HIV-related outcomes, we included clinical outcomes that may influence retention in care, ART adherence, and viral suppression – including depression, anxiety, non-routine care visits, unmet needs for care services, and healthcare-related discrimination. Symptoms of depression and generalized anxiety disorder (GAD) during the past 2 weeks were assessed using previously validated scales (Patient Health Questionnaire-8 and Generalized Anxiety Disorder-7, respectively) and categorized based on clinically meaningful cutpoints (Spitzer et al., 1999; Spitzer et al., 2006). Participants were asked about emergency room (ER) visits and hospitalizations during the previous 12 months. Unmet needs for ancillary care services, such as dental care, HIV case management, and patient navigation services, were defined as persons needing, but not receiving, services during the past 12 months (CDC, 2019). Respondents were considered to have experienced healthcare discrimination if they reported that, since testing HIV-positive, anyone in the healthcare system: (1) exhibited hostility or lack of respect towards them, (2) was less attentive towards them than other patients, and/or (3) refused them services. PWID who reported experiencing healthcare discrimination were asked whether they attributed the discrimination to their injection drug use.

Analysis

Data from the 2015, 2016, and 2017 cycles were combined for the analysis. We reported demographic characteristics and social determinants of health among HIV-positive PWID (N=340) and HIV-positive persons who do not inject drugs (N=11,475) using weighted percentages and 95% confidence intervals (CIs). We reported prevalence ratios (PRs) with predicted marginal means to compare differences in characteristics by injection drug use status, using α=.05 as the cutoff for statistical significance.

Next, we assessed associations between injection drug use and clinical outcomes, including (1) those directly related to HIV (e.g., retention in care, ART adherence, viral suppression) and (2) those that may influence HIV outcomes (e.g., depression, anxiety, use of non-routine care visits). Since certain social determinants of health have been found to be associated with clinical outcomes in the literature, PRs were adjusted for age, race/ethnicity, and gender to control for potential confounding (CDC, 2019, 2020). Because the models with clinical outcomes involved multiple statistical tests, we presented adjusted PRs with corresponding 95% confidence intervals, but highlighted covariates in models that remained statistically significant even after multiple comparisons adjustment using the Bonferroni correction.

Data were weighted based on known probabilities of selection, adjusted for non-response, and post-stratified to NHSS population totals by age, race/ethnicity, and sex at birth. All analyses were conducted using SAS, version 9.4 (SAS Institute, Cary, NC) and SAS-callable SUDAAN, version 11.0.3 (RTI International, NC).

Results

Overall, 2.6% of adults with diagnosed HIV injected drugs in the prior 12 months (Table 1). Compared with persons who do not inject drugs, PWID were more likely to be male (92.1% vs. 75.4%) and non-Hispanic white (57.0% vs. 29.0%). PWID were 3.59 times as likely to be homeless (29.1% vs. 8.1%) and 3.75 times as likely to be incarcerated in the past 12 months (18.3% vs. 4.9%), compared with persons who do not inject drugs. PWID were less likely to have private health insurance than other persons (27.1% vs. 35.6%).

Table 1.

Demographic characteristics and social determinants of health among HIV-positive persons who inject drugs (PWID) (n=340) and persons who do not inject drugs (n=11,475) – Medical Monitoring Project, 2015–2018.*

Characteristic HIV-positive PWID HIV-positive non-PWID Unadjusted PR P
n Weighted col % (95% CI) N Weighted col % (95% CI)
Total (row %) 340 2.6 (2.1–3.2) 11,475 97.4 (96.8–97.9) -- --
Age, in years
18–29 27 10.5 (6.8–14.2) 953 8.9 (8.1–9.8) 1.18 (0.81–1.71) 0.393
30–39 86 26.3 (20.3–32.2) 1840 16.2 (15.4–17.1) 1.62 (1.28–2.04) <0.001
40–49 85 22.9 (17.4–28.4) 2774 24.7 (23.7–25.7) 0.93 (0.73–1.17) 0.525
≥50 142 40.3 (33.7–46.9) 5908 50.1 (48.7–51.5) 0.80 (0.69–0.94) 0.003
Gender
Male 305 92.1 (88.9–95.4) 8308 75.4 (73.9–76.9) 1.22 (1.18–1.27) <0.001
Female 32 7.9 (4.6–11.1) 2992 24.6 (23.1–26.1) --
Race/ethnicity
White, non-Hispanic 197 57.0 (49.1–64.8) 3312 29.0 (25.6–32.3) 1.97 (1.72–2.25) <0.001
Black, non-Hispanic 52 14.3 (8.6–20.1) 4882 41.6 (36.3–47.0) 0.34 (0.24–0.50) <0.001
Hispanic/Latino 64 20.3 (13.8–26.9) 2513 22.5 (18.0–27.0) 0.91 (0.65–1.26) 0.553
Other 27 8.4 (4.4–12.3) 768 6.9 (6.0–7.9) 1.20 (0.78–1.85) 0.404
Poverty threshold
Above poverty threshold 159 52.8 (45.6–59.9) 6020 56.8 (54.3–59.4) --
At or below poverty threshold 164 47.2 (40.1–54.4) 4713 43.2 (40.6–45.7) 1.09 (0.93–1.29) 0.287
Health insurance coverage
Any private 88 27.1 (21.4–32.9) 4007 35.6 (33.7–37.5) 0.76 (0.61–0.95) 0.011
Public only, excluding RWHAP/ADAP only 224 59.8 (52.5–67.1) 6367 54.2 (51.9–56.4) 1.10 (0.97–1.26) 0.161
RWHAP/ADAP only or no coverage 26 13.1 (6.4–19.7) 994 10.2 (8.4–12.0) 1.28 (0.77–2.12) 0.351
Homelessness
Yes 102 29.1 (22.7–35.6) 952 8.1 (7.4–8.8) 3.59 (2.85–4.52) <0.001
No 237 70.9 (64.4–77.3) 10,523 91.9 (91.2–92.6) --
Incarceration
Yes 58 18.3 (13.2–23.4) 539 4.9 (4.3–5.5) 3.75 (2.79–5.04) <0.001
No 282 81.7 (76.6–86.8) 10,931 95.1 (94.5–95.7) --
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Notes:

*

Injection drug use was based on the past 12 months. All characteristics were based on the past 12 months, unless otherwise indicated.

Abbreviations: PWID: persons who inject drugs; RWHAP: Ryan White HIV/AIDS Program; ADAP: AIDS Drug Assistance Program.

We present associations between injection drug use in the past 12 months and clinical characteristics, controlling for age, gender, and race/ethnicity in Table 2. Compared with persons who do not inject drugs, PWID were less likely to be retained in HIV care (aPR: 0.85; 95% CI: 0.77–0.94) and have sustained viral suppression (aPR: 0.75; 95% CI: 0.66–0.85). PWID were more likely to not take ART (aPR: 2.53; 95% CI: 1.79–3.56) and less likely to be 100% ART adherent (aPR: 0.51; 95% CI: 0.41–0.64).

Table 2.

HIV care continuum outcomes and other clinical outcomes among HIV-positive persons who inject drugs (PWID) (n=340) and persons who do not inject drugs (n=11,475) – Medical Monitoring Project, 2015–2018.*

Characteristic HIV-positive PWID HIV-positive non-PWID Unadjusted PR P Adjusted PRa P
n Weighted col % (95% CI) n Weighted col % (95% CI)
Total (row %) 340 2.6 (2.1–3.2) 11,475 97.4 (96.8–97.9) – -- – –
HIV CONTINUUM OF CARE OUTCOMES
Retention in HIV careb
Yes 261 65.9 (59.2–72.6) 9589 79.8 (78.4–81.3) 0.83 (0.75–0.91) <0.001 0.85 (0.77–0.94) <0.001
No 74 34.1 (27.4–40.8) 1595 20.2 (18.7–21.6) – –
ART use and adherence
Not currently taking ARTb 40 20.2 (13.6–26.8) 597 7.9 (7.2–8.7) 2.55 (1.81–3.58) <0.001 2.53 (1.79–3.56) <0.001
Currently taking ART but not adherent 223 59.0 (52.6–65.4) 6095 51.5 (50.2–52.8) 1.15 (1.03–1.28) 0.025 1.15 (1.03–1.29) 0.024
Currently taking ART and 100% adherentb 77 20.8 (16.1–25.5) 4730 40.6 (39.2–41.9) 0.51 (0.41–0.64) <0.001 0.51 (0.41–0.64) <0.001
Sustained viral suppressionb
Yes 188 48.1 (41.9–54.4) 7856 64.4 (62.7–66.1) 0.75 (0.66–0.85) <0.001 0.75 (0.66–0.85) <0.001
No 152 51.9 (45.6–58.1) 3619 35.6 (33.9–37.3) – –
CLINCIAL OUTCOMES THAT MAY AFFECT HIV CONTINUUM OF CARE
Moderate/severe generalized anxiety disorderb
Yes 110 33.7 (27.1–40.4) 1910 17.3 (16.3–18.3) 1.95 (1.59–2.39) <0.001 2.01 (1.65–2.44) <0.001
No 229 66.3 (59.6–72.9) 9512 82.7 (81.7–83.7) – –
Major or other depressionb
Yes 124 35.9 (29.6–42.2) 2327 21.2 (20.0–22.4) 1.69 (1.40–2.04) <0.001 1.76 (1.47–2.10) <0.001
No 214 64.1 (57.8–70.4) 9062 78.8 (77.6–80.0) – –
Had unmet need for ≥1 serviceb
Yes 272 79.2 (73.3–85.2) 6024 53.7 (52.4–55.0) 1.48 (1.36–1.59) <0.001 1.50 (1.39–1.61) <0.001
No 68 20.8 (14.8–26.7) 5442 46.3 (45.0–47.6) – –
Had ≥1 emergency room visitb
Yes 188 54.9 (48.9–60.9) 4270 37.3 (35.6–38.9) 1.47 (1.31–1.65) <0.001 1.51 (1.35–1.69) <0.001
No 151 45.1 (39.1–51.1) 7176 62.7 (61.1–64.4) – –
Had ≥1 hospitalizationb
Yes 108 27.6 (21.7–33.4) 1988 16.9 (15.9–17.9) 1.63 (1.32–2.02) <0.001 1.78 (1.46–2.17) <0.001
No 232 72.4 (66.6–78.3) 9461 83.1 (82.1–84.1) – –
Experienced healthcare discrimination after HIV diagnosisb
Yes 112 31.5 (25.7–37.3) 2499 22.1 (20.9–23.3) 1.42 (1.18–1.72) 0.001 1.42 (1.17–1.73) 0.001
No 225 68.5 (62.7–74.3) 8903 77.9 (76.7–79.1) –
Discrimination attributed to injection drug use among persons who experienced healthcare discrimination after HIV diagnosisb
Yes 49 39.7 (29.9–49.5) – – – – – –
No 62 60.3 (50.5–70.1) – – – –
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Notes:

*

Injection drug use was based on the past 12 months. All characteristics were based on the past 12 months, unless otherwise indicated.

a

Results adjusted for age, race/ethnicity, and gender.

b

Association remained significant after Bonferroni correction for multiple comparisons.

Abbreviations: PWID: persons who inject drugs; ART: antiretroviral therapy.

PWID were more likely to have an unmet need for ancillary care services (aPR: 1.50; 95% CI: 1.39–1.61) and to self-report ER visits (PR: 1.51; 95% CI: 1.35–1.69) and hospitalizations (aPR: 1.78; 95% CI: 1.46–2.17), compared with other persons. PWID had higher levels of moderate or severe GAD (aPR: 2.01; 95% CI: 1.65–2.44) and major or other depression (aPR: 1.76; 95% CI: 1.47–2.10). PWID were more likely to have experienced healthcare discrimination following HIV diagnosis (aPR: 1.42; 95% CI: 1.17–1.73); among HIV-positive PWID who experienced discrimination, nearly 40% attributed the discrimination to injection drug use.

Discussion

This is the first analysis to compare nationally representative estimates of characteristics among U.S. HIV-positive PWID and HIV-positive persons who do not inject drugs. We found that HIV-positive PWID were more likely to be homeless and incarcerated. HIV-positive PWID had poorer outcomes related to HIV, including ART use, ART adherence, and viral suppression, and outcomes not directly related to HIV, such as GAD and depression. HIV-positive PWID were less likely to be engaged in routine HIV care, and were more likely to have unmet needs for ancillary care services, visit the ER, and be hospitalized.

Having a routine source of care and adequate healthcare coverage are key predictors of early ART initiation among HIV-positive PWID, a key facilitator for achieving viral suppression and decreasing HIV transmission risk (Mehta et al., 2010). Routine HIV care for PWID is also critical because PWID can experience a number of comorbidities. Coinfections related to drug use, such as hepatitis C and bacterial endocarditis, are common, could result in complications if untreated, and could accelerate HIV clinical disease progression (Bruce & Altice, 2007; Sulkowski, 2007). Further, depression, which we found to be more prevalent among HIV-positive PWID, is associated with poor HIV outcomes along the continuum of care (Beer et al., 2019; Gokhale R et al., 2019) and drug overdose (Bartoli et al., 2014).

Having unmet needs for ancillary services could lead to poor outcomes across the HIV care continuum, from linkage to care to achieving and maintaining viral suppression. Unmet needs for care could also necessitate emergency care visits for acute medical issues related to drug use, such as overdose or endocarditis (Bruce & Altice, 2007), or because there is simply no other source for routine care. This is particularly important given the recent large increases in opioid-involved overdose deaths, driven primarily by deaths involving illicitly manufactured fentanyl and fentanyl analogs (Wilson et al., 2020). PWID may be less likely to receive routine HIV care because of competing priorities and social stressors related to drug use and poor access to healthcare, which contribute to virologic failure (Bruce & Altice, 2007; Meyer et al., 2013). Incarceration and unstable housing, which are more common among HIV-positive PWID than HIV-positive persons who do not inject drugs, could interrupt healthcare coverage and continuity of HIV care, and impede ART adherence (Milloy et al., 2011). This may especially true for persons with HIV who are caught in a cycle between incarceration and release. Providing referrals for care when released from jail or prison and linking patients to navigation services can help ensure that care and access to ART remain continuous (Cunningham et al., 2018).

HIV-positive PWID often experience stigma and discrimination related to injection drug use and addiction, mental illness, and HIV, which can, in turn, worsen health outcomes (Ahern et al., 2007; Barry et al., 2014). Marginalization of PWID can also be seen in the healthcare setting in the form of healthcare-related discrimination, which be a deterrent to establishing strong connections between providers and patients, and can discourage PWID from engaging with the healthcare system. Establishing strong patient-provider relationships helps ensure that trust is built between providers and patients, and that patients are connected to healthcare services based on their needs (Knowlton et al., 2010). Increased availability of provider trainings focused on decreasing healthcare discrimination among HIV-positive PWID may help strengthen patient-provider relationships and provision of patient-centered care.

We demonstrated that HIV-positive PWID were less likely to use ART, compared with other persons. Although injection drug use has been associated with delayed ART initiation in other settings (Mehta et al., 2010), positive patient-provider relationships have been shown to be associated with earlier ART initiation among HIV-positive PWID (Knowlton et al., 2010). However, a survey conducted in 2012 demonstrated that about a quarter of sampled HIV care providers reported that they would defer ART for HIV-positive PWID because of concerns around adherence and treatment readiness (Westergaard et al., 2012). A more recent analysis demonstrated that 64% of providers were aware of national guidelines recommending ART initiation regardless of disease stage or history of pre-existing conditions, such as mental illness, substance use, or psychosocial challenges (HHS, 2019; Krakower et al., 2015). However, over three-fourths of providers reported that they would defer treatment if patients were not ready to initiate ART (Krakower et al., 2015). International guidelines on HIV care management also indicate that ART should be initiated at or shortly after HIV diagnosis (WHO, 2017). Patients with a history of homelessness and substance use, who may be more likely to have interruptions in care, should be offered additional support through case management to ensure ART adherence (HHS, 2019). Offering case management through other community members that may have previously injected drugs or experienced homelessness may be helpful in providing more support for HIV-positive PWID who may have experienced similar circumstances. Emphasizing the importance of early or immediate ART initiation and provision of ART adherence support services during provider trainings could improve treatment success among HIV-positive PWID.

Given that HIV-positive PWID experience multiple challenges to accessing medical care and managing health outcomes, expanding availability of co-located ancillary care services, such as for HIV case management, mental health, and substance use disorder treatment, that are available during flexible hours and in easily accessible locations may improve HIV care engagement (Meyer et al., 2013; Smith-Rohrberg et al., 2006). Increasing access to medication-assisted treatment for substance use disorders in a facility with co-located services, such as a syringe services program (SSP), could reduce need for injection, thus decreasing HIV transmission risk, improving ART adherence (Meyer et al., 2013), and closing the gap in health disparities between HIV-positive PWID and persons who do not inject drugs. SSPs not only provide access to clean syringes and other injection equipment, but also offer a forum for provision of comprehensive prevention services and referrals for services not offered on-site (CDC, 2017; Strathdee et al., 1997). Co-locating HIV treatment and support services in SSPs is part of a comprehensive, integrated HIV prevention approach and supports the Ending the HIV Epidemic initiative.

There were some limitations to this analysis. First, not all sampled persons participated in MMP, but results were adjusted for nonresponse and post-stratified to known population totals by age, race/ethnicity, and gender from the National HIV Surveillance System using standard methodology. Because we took simple random samples of adults with diagnosed HIV from selected jurisdictions by data cycle, people had the potential of being selected, and participating, in more than one MMP cycle; however, the proportion of people who participated in multiple data cycles was low (3%). All characteristics ascertained through interview were based on self-report, and thus, subject to information bias. However, we do not suspect that misclassification was differential with respect to history of injection drug use; thus, results may be biased towards the null.

Conclusions

HIV-positive PWID had poorer social determinants of health and clinical outcomes, compared with HIV-positive persons who do not inject drugs. HIV-positive PWID were less engaged in routine HIV care, and had greater unmet needs for care services and more non-routine care visits. Given the challenges that HIV-positive PWID face, enhancing availability of services to match the needs of this population may be helpful in improving outcomes. Further, interventions supporting (1) continuity of care given high levels of incarceration and housing instability, (2) programs focused on early ART initiation following HIV diagnosis and provision of ART adherence support, and (3) drug treatment and harm reduction programs to limit transmission risk among HIV-positive PWID, are important for supporting the Ending the HIV Epidemic initiative.

Funding

This work was funded by Centers for Disease Control and Prevention

Footnotes

Disclosure statement

No potential conflict of interest was reported by the author(s).

References

  1. Adler NE, & Newman K (2002). Socioeconomic disparities in health: Pathways and policies. Health Affairs, 21(2), 60–76. 10.1377/hlthaff.21.2.60. [DOI] [PubMed] [Google Scholar]
  2. Ahern J, Stuber J, & Galea S (2007). Stigma, discrimination and the health of illicit drug users. Drug and Alcohol Dependence, 88(2–3), 188–196. 10.1016/j.drugalcdep.2006.10.014 [DOI] [PubMed] [Google Scholar]
  3. Altice FL, Kamarulzaman A, Soriano VV, Schechter M, & Friedland GH (2010). Treatment of medical, psychiatric, and substance-use comorbidities in people infected with HIV who use drugs. The Lancet, 376(9738), 367–387. 10.1016/S0140-6736(10)60829-X [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Barry CL, McGinty EE, Pescosolido BA, & Goldman HH (2014). Stigma, discrimination, treatment effectiveness, and policy: Public views about drug addiction and mental illness. Psychiatric Services, 65(10), 1269–1272. 10.1176/appi.ps.201400140 [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Bartoli F, Carra G, Brambilla G, Carretta D, Crocamo C, Neufeind J, Baldacchino A, Humphris G, & Clerici M (2014). Association between depression and non-fatal overdoses among drug users: A Systematic review and meta-analysis. Drug and Alcohol Dependence, 134, 12–21. 10.1016/j.drugalcdep.2013.10.007 [DOI] [PubMed] [Google Scholar]
  6. Beer L, Tie Y, Padilla M, & Shouse RL (2019). Generalized anxiety disorder symptoms among persons with diagnosed HIV in the United States-2015–2016, Medical Monitoring Project. AIDS (London, England). 10.1097/QAD.0000000000002286. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Bradford JB, Coleman S, & Cunningham W (2007). HIV system navigation: An emerging model to improve HIV care access. AIDS Patient Care and STDs, 21(Suppl 1), S49–S58. 10.1089/apc.2007.9987 [DOI] [PubMed] [Google Scholar]
  8. Bruce RD, & Altice FL (2007). Clinical care of the HIV-Infected drug user. Infectious Disease Clinics of North America, 21(1), 149–179. doi: 10.1016/j.idc.2007.03.009. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. CDC. (2017). HIV Surveillance report, 2017. https://www.cdc.gov/hiv/pdf/library/reports/surveillance/cdc-hivsurveillance-report-2017-vol-29.pdf
  10. CDC. (2017). Reducing harms from injection drug use & opioid use disorder with syringe services programs.
  11. CDC. (2019). Behavioral and clinical characteristics of persons with diagnosed HIV infection–Medical Monitoring Project, United States, 2016 cycle (June 2016-May 2017). HIV Surveillance Special Report 21. [Google Scholar]
  12. CDC. (2020).HIV infection risk, prevention, and testing behaviors among persons who inject drugs—National HIV Behavioral Surveillance: Injection Drug Use, 23 U.S. Cities, 2018. https://www.cdc.gov/hiv/pdf/library/reports/surveillance/cdc-hivsurveillance-special-report-number-24.pdf
  13. Cohen MS, Chen YQ, McCauley M, Gamble T, Hosseinipour MC, Kumarasamy N, Hakim JG, Kumwenda J, Grinsztejn B, Pilotto JHS, Godbole SV, Chariyalertsak S, Santos BR, Mayer KH, Hoffman IF, Eshleman SH, Piwowar-Manning E, Cottle L, Zhang XC, … Team HS (2016). Antiretroviral therapy for the prevention of HIV-1 transmission. New England Journal of Medicine, 375(9), 830–839. 10.1056/NEJMoa1600693 [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Colasanti J, Stahl N, Farber EW, Del Rio C, & Armstrong WS (2017). An exploratory study to assess individual and structural level barriers associated with poor retention and re-engagement in care among persons living with HIV/AIDS. Journal of Acquired Immune Deficiency Syndromes, 74(Suppl 2), S113–S120. 10.1097/QAI.0000000000001242. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Cranston K, Alpren C, John B, Dawson E, Roosevelt K, Burrage A, Bryant J, Switzer WM, Breen C, Peters PJ, Stiles T, Murray A, Fukuda HD, Adih W, Goldman L, Panneer N, Callis B, Campbell EM, Randall L, … DeMaria A (2019). Notes from the field: HIV diagnoses among persons who inject drugs -Northeastern Massachusetts, 2015–2018. MMWR. Morbidity and Mortality Weekly Report, 68(10), 253–254. 10.15585/mmwr.mm6810a6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Crepaz N, Tang T, Marks G, Mugavero MJ, Espinoza L, & Hall HI (2016). Durable viral suppression and transmission risk potential among persons with diagnosed HIV infection: United States, 2012–2013. Clinical Infectious Diseases, 63(7), 976–983. 10.1093/cid/ciw418. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Cunningham WE, Weiss RE, Nakazono T, Malek MA, Shoptaw SJ, Ettner SL, & Harawa NT (2018). Effectiveness of a peer navigation intervention to sustain viral suppression among HIV-positive men and transgender women released from jail: The LINK LA Randomized clinical Trial. JAMA Internal Medicine, 178(4), 542–553. 10.1001/jamainternmed.2018.0150 [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. DHHS. (2014). Computations for the 2014 annual update of the HHS poverty guidelines for the 48 contiguous states and the District of Columbia. https://aspe.hhs.gov/computations-2014-annual-update-hhs-poverty-guidelines-48-contiguous-states-and-district-columbia.
  19. DHHS. (2015). Poverty guidelines. https://aspe.hhs.gov/2015-poverty-guidelines
  20. DHHS. (2016) Computations for the 2016 poverty guidelines. https://aspe.hhs.gov/computations-2016-poverty-guidelines
  21. Gokhale R, Weiser J, Sullivan PS, Luo Q, Shu F, & Bradley H (2019). Depression prevalence, antidepressant treatment status, and association with sustained HIV viral suppression among adults living with HIV in care in the United States, 2009–2014. AIDS and Behavior. 10.1007/s10461-019-02613-6 [DOI] [PubMed] [Google Scholar]
  22. Golden MR, Lechtenberg R, Glick SN, Dombrowski J, Duchin J, Reuer JR, Dhanireddy S, Neme S, & Buskin SE (2019). Outbreak of human immunodeficiency virus infection among heterosexual persons who are living homeless and inject drugs – Seattle, Washington, 2018. MMWR. Morbidity and Mortality Weekly Report, 68(15), 344–349. 10.15585/mmwr.mm6815a2 [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. HHS. (2019). Guidelines for the use of antiretroviral agents in adults and adolescents with HIV.
  24. Kamarulzaman A, & Altice FL (2015). Challenges in managing HIV in people who use drugs. Current Opinion in Infectious Diseases, 28(1), 10–16. 10.1097/QCO.0000000000000125 [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Knowlton AJ, Eldred LJ, Wilkinson JD, Shade SB, Bohnert AS, Yang C, Wissow LS, & Purcell DW (2010). Antiretroviral use among active injection-drug users: The role of patient-provider engagement and structural factors. AIDS Patient Care and STDs, 24(7), 421–428. 10.1089/apc.2009.0240 [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Krakower DS, Oldenburg CE, Mitty JA, Wilson IB, Kurth AE, Maloney KM, Gallagher D, & Mayer KH (2015). Knowledge, beliefs and practices regarding antiretroviral medications for HIV prevention: results from a survey of healthcare providers in New England. PLoS One, 10(7), e0132398. 10.1371/journal.pone.0132398 [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Lewden C, Chene G, Morlat P, Raffi F, Dupon M, Dellamonica P, Pellegrin J-L, Katlama C, Dabis F, Leport C, & Agence Nationale de Recherches sur le Sida et les Hepatites Virales (2007). HIV-infected adults with a CD4 cell count greater than 500 cells/mm3 on long-term combination antiretroviral therapy reach same mortality rates as the general population. JAIDS Journal of Acquired Immune Deficiency Syndromes, 46(1), 72–77. 10.1097/QAI.0b013e318134257a [DOI] [PubMed] [Google Scholar]
  28. Lucas GM, Cheever LW, Chaisson RE, & Moore RD (2001). Detrimental effects of continued illicit drug use on the treatment of HIV-1 infection. Journal of Acquired Immune Deficiency Syndromes, 27(3), 251–259. 10.1097/00042560-200107010-00006 [DOI] [PubMed] [Google Scholar]
  29. Mehta SH, Kirk GD, Astemborski J, Galai N, & Celentano DD (2010). Temporal trends in highly active antiretroviral therapy initiation among injection drug users in Baltimore, Maryland, 1996–2008. Clinical Infectious Diseases, 50(12), 1664–1671. 10.1086/652867 [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Meyer JP, Althoff AL, & Altice FL (2013). Optimizing care for HIV-Infected people who use drugs: evidence-based approaches to overcoming healthcare disparities. Clinical Infectious Diseases, 57(9), 1309–1317. 10.1093/cid/cit427 [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Milloy MJ, Kerr T, Buxton J, Rhodes T, Guillemi S, Hogg R, Montaner J, & Wood E (2011). Dose-response effect of incarceration events on nonadherence to HIV antiretroviral therapy among injection drug Users. The Journal of Infectious Diseases, 203(9), 1215–1221. 10.1093/infdis/jir032 [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Mugavero MJ, Amico KR, Westfall AO, Crane HM, Zinski A, Willig JH, Dombrowski JC, Norton WE, Raper JL, Kitahata MM, & Saag MS (2012). Early retention in HIV care and viral load suppression: Implications for a test and treat approach to HIV prevention. JAIDS Journal of Acquired Immune Deficiency Syndromes, 59(1), 86–93. 10.1097/QAI.0b013e318236f7d2 [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Nandi A, Glass TA, Cole SR, Chu H, Galea S, Celentano DD, Kirk GD, Vlahov D, Latimer WW, & Mehta SH (2010). Neighborhood poverty and injection cessation in a sample of injection drug Users. American Journal of Epidemiology, 171(4), 391–398. 10.1093/aje/kwp416 [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Palepu A, Tyndall M, Yip B, O’Shaughnessy MV, Hogg RS, & Montaner JS (2003). Impaired virologic response to highly active antiretroviral therapy associated with ongoing injection drug use. JAIDS Journal of Acquired Immune Deficiency Syndromes, 32(5), 522–526. 10.1097/00126334-200304150-00009 [DOI] [PubMed] [Google Scholar]
  35. Peters PJ, Pontones P, Hoover KW, Patel MR, Galang RR, Shields J, Blosser SJ, Spiller MW, Combs B, Switzer WM, Conrad C, Gentry J, Khudyakov Y, Waterhouse D, Owen SM, Chapman E, Roseberry JC, & McCants V (2016). HIV infection linked to injection use of oxymorphone in Indiana, 2014–2015. New England Journal of Medicine, 375(3), 229–239. 10.1056/NEJMoa1515195. [DOI] [PubMed] [Google Scholar]
  36. Smith-Rohrberg D, Mezger J, Walton M, Bruce RD, & Altice FL (2006). Impact of enhanced services on virologic outcomes in a directly administered antiretroviral therapy trial for HIV-Infected drug users. JAIDS Journal of Acquired Immune Deficiency Syndromes, 43(Suppl 1), S48–S53. 10.1097/01.qai.0000248338.74943.85. [DOI] [PubMed] [Google Scholar]
  37. Spitzer RL, Kroenke K, & Williams JB (1999). Validation and utility of a self-report version of PRIME-MD: The PHQ primary care study. Primary Care Evaluation of Mental Disorders. Patient Health Questionnaire. JAMA, 282(18), 1737–1744. 10.1001/jama.282.18.1737. [DOI] [PubMed] [Google Scholar]
  38. Spitzer RL, Kroenke K, Williams JB, & Lowe B (2006). A brief measure for assessing generalized anxiety disorder: The GAD-7. Archives of Internal Medicine, 166 (10), 1092–1097. 10.1001/archinte.166.10.1092 [DOI] [PubMed] [Google Scholar]
  39. Strathdee SA, Patrick DM, Currie SL, Cornelisse PG, Rekart ML, Montaner JS, Schechter MT, & O’Shaughnessy MV (1997). Needle exchange is not enough: lessons from the Vancouver injecting drug use study. AIDS (London, England), 11(8), F59–F65. 10.1097/00002030-199708000-00001. [DOI] [PubMed] [Google Scholar]
  40. Sulkowski MS (2007). Hepatitis C virus infection in HIV-infected patients. Current Infectious Disease Reports, 3(5), 469–476. 10.1007/s11908-007-1004-1. [DOI] [PubMed] [Google Scholar]
  41. Westergaard RP, Ambrose BK, Mehta SH, & Kirk GD (2012). Provider and clinic-level correlates of deferring antiretroviral therapy for people who inject drugs: A survey of North American HIV providers. Journal of the International AIDS Society, 15(1), 10. 10.1186/1758-2652-15-10 [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. WHO. (2017). Guidelines for managing advanced HIV disease and rapid initiation of antiretroviral therapy. [PubMed]
  43. Wilson N, Kariisa M, Seth P, Smith HT, & Davis NL (2020). Drug and opioid-involved overdose deaths -United States, 2017–2018. MMWR. Morbidity and Mortality Weekly Report, 69(11), 290–297. 10.15585/mmwr.mm6911a4 [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Zibbell JE, Asher AK, Patel RC, Kupronis B, Iqbal K, Ward JW, & Holtzman D (2018). Increases in acute hepatitis C virus infection related to a growing opioid epidemic and associated injection drug use, United States, 2004–2014. American Journal of Public Health, 108(2), 175–181. doi: 10.2105/AJPH.2017.304132 [DOI] [PMC free article] [PubMed] [Google Scholar]

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