Community-based DOT-HAART Accompaniment in an Urban Resource-Poor Setting

Abstract

From December 2005 to April 2007, we enrolled 60 adults starting antiretroviral therapy (ART) in a health district of Lima, Peru to receive community-based accompaniment with supervised antiretroviral (CASA). Paid community health workers performed twice-daily home visits to directly observe ART and offered additional medical, social and economic support to CASA participants. We matched 60 controls from a neighboring district by age, CD4 and primary referral criteria (TB status, female, neither). Using validated instruments at baseline and 12 months (time of DOT-HAART completion) we measured depression, social support, quality of life, HIV-related stigma and self-efficacy. We compared 12 month clinical and psychosocial outcomes among CASA versus control groups. CASA participants experienced better clinical and psychosocial outcomes at 12 months, including proportion with virologic suppression, increase in social support and reduction in HIV-associated stigma.

Introduction

One of the strongest predictors of HIV clinical outcomes, nonadherence to high active antiretroviral therapy (HA-ART) is associated with excess morbidity and mortality (Mills et al. 2006). From the public health perspective, nonadherence results in a costly, chronic pool of patients who contribute to primary transmission of drug-resistant strains (Wainberg and Friedland 1998). Although HAART programs in resource-poor settings have reported excellent adherence rates (Byakika-Tusiime et al. 2003; Mills et al. 2006; Muyingo et al. 2008), in reality achieving excellent adherence to HIV treatment requires both retention on HAART as well as HAART adherence among those who stay on treatment. In resource-poor settings where individuals face socioeconomic instability and limited antiretroviral options, sustained HIV treatment adherence is all the more crucial and challenging. Unfortunately, emerging data on rising rates of virologic failure and loss to follow-up reflect the challenges of both HAART adherence and retention as national programs in such settings expand (Larsson et al. 2007; Rosen et al. 2007; Spacek et al. 2006; Tuboi et al. 2005; van Oosterhout et al. 2005).

The socio-ecological model posits that behavior is influenced by embedded, dynamic, and interconnected social spheres, from personal factors to close social networks to larger fields such as cultural, community and policy factors (Bronfenbrenner 1979). We have argued that the “accompagnateur” model addresses adherence barriers within a socio-ecological model (Castro 2005). We define the term accompaniment as medical, social and economic support delivered by paid community-based health workers (Farmer et al. 2001). Community-based directly observed antiretroviral therapy (DOT-HAART), an integral component of accompaniment, helps address daily barriers to pill-taking, provides emotional and informational support, and serves as a liaison with formal health services (Mukherjee et al. 2006). We now provide community-based accompaniment with supervised antiretrovirals (CASA) to over 12,000 patients in Boston, rural Haiti, Rwanda and elsewhere, with excellent adherence and clinical outcomes (Behforouz et al. 2004; Koenig et al. 2004; Partners In Health 2008). Nonetheless, whether DOT-HAART should be implemented in resource-poor settings remains controversial. Some speculate about paradoxically increasing drug resistance, worry that stigma poses an insurmountable barrier to DOT-HAART in poor communities, and question whether DOT-HAART is even needed given higher overall adherence rates in such settings (Liechty and Bangsberg 2003). Unfortunately, emerging data likely marks the end of our “honeymoon” period of high adherence in early treatment cohorts in resource-poor settings. Low patient retention and trends of rising nonadherence serve as a “wake-up call” for the need to improve adherence in these regions (Bisson et al. 2008; Chen et al. 2008; Gill et al. 2005; Phillips et al. 2007; Wakabi 2008).

In 1996, we started a partnership between our Peru-based organization, Socios En Salud, with the Peruvian Ministry of Health to provide community-based directly observed therapy of multidrug-resistant tuberculosis (MDR-TB). Based on this strong community network and public-private alliance, we initiated a pilot in 2005 to provide 12 months of CASA support to patients starting antiretroviral therapy in a single health district of Lima, Peru. Here, we describe the clinical and psychosocial outcomes among HIV-positive adults at 12 months receiving CASA, compared with a matched control group selected from a neighboring health district.

Methods

Setting and Recruitment

Peru has an HIV prevalence of 0.6% and an estimated 60,000–80,000 HIV-positive individuals as of 2005 (Population Reference Bureau 2006). In collaboration with the National HIV Program, we enrolled 95 adult patients between December 2005 and April 2007. All patients were referred from a tertiary public hospital, which provides HIV care and antiretroviral therapy to the health region of Lima Este (total population 1,856,514 inhabitants). Providers referred patients living in poverty and who were starting or had recently started HAART. In response to the needs cited by local providers and our community-based team, enrollment priority was given to individuals who were co-infected with TB or female. However, males without TB co-infection were not excluded. For each patient enrolled in DOT-HAART, we sought a matched control in tertiary hospital serving a neighboring health region (Lima Ciudad). Because of limited funds, we enrolled the first 60 controls that could be successfully matched to our cohort. Controls were chosen among those eligible for HAART during the same period and were matched to cases by baseline characteristics of age (±5 years), primary referral criteria (TB, woman, neither), and CD4 cell count (≤ or >200 cells/ml³). All patients provided informed consent. Patients were excluded if they lived outside their respective hospitals’ catchment area.

Intervention Description

DOT-HAART participants were assigned a DOT worker. The community-based team also included a team of 12 field supervisors and two nurses. Nurses coordinated patient care with National and District program leaders and health professionals, monitored clinical and psychosocial follow-up, and supervised team activities and training. Field supervisors consisted of lay individuals who often had prior community leadership roles. Responsible for ~20 patients 3–4 DOT volunteers, field supervisors visited health establishments to arrange appointments and inform providers of patient-related issues; monitored DOT; provided clinical and social support through home and hospital visits and patient accompaniment to outpatient appointments, reported activities and events to nurses and providers; and conducted household contact screening for risk factors and/or symptoms of HIV and TB. DOT workers were selected by Ministry of Health providers, and were usually individuals living in the community who had prior experience working as community health workers for local health establishments. Caseload was usually 3–4 patients who lived near the worker’s residence. DOT workers were responsible for supervising all outpatient HAART doses in patients’ homes or elsewhere if by the patient, for which they were compensated with monthly food baskets. Workers also supervised ingestion of other medications (e.g., for opportunistic infections, diabetes, psychiatric disorders, tuberculosis, etc.), and reported any missed doses, adverse events and/or psychosocial crises to nurses and providers. During DOT encounters, workers provided patients and family members with emotional support, health education and screening for HIV- and/or medication-related symptoms. The team helped coordinate follow-up appointments, communicated patient issues to providers, and carried out physician indications by helping the patient obtain laboratory testing and medications. The entire team underwent 4 days of initial training, reviewing Ministry HIV services; HIV and antiretroviral medications; principles of adherence and the role of DOT; and issues in mental health, domestic violence, and substance use. The support lasted 12 months, with tapered DOT visits during the last 2 months. Patients also received comprehensive support, including financial aide for diagnostic tests and medications to treat opportunistic infections and adverse reactions, transportation and nutritional support, as needed. Phase two of the pilot will provide matched social support (i.e., peer group therapy and/or microfinance assistance based on a needs assessment) in year two and assess outcomes at 24 months (See Fig. 1).

Fig. 1.

Description and time-line of community-based intervention

Routine Care

Patients are evaluated for HIV when they present to health services with clinical suggestions and/or risk factors for HIV. Voluntary counseling and testing is offered at health centers and hospitals. Free CD4 count and HIV viral load are performed upon diagnosis. Patients are evaluated for opportunistic infections, including TB by sputum smear microscopy, culture and chest radiograph. A psychosocial evaluation includes a peer counseling session and evaluation by both a psychologist and social worker. HAART is initiated based on WHO criteria (World Health Organization 2003). In order to initiate HAART, patients are required to identify a treatment supporter (“agente de soporte”) who is responsible for providing emotional support around medication adherence and accompanying patients to their medical visits. The treatment supporter does not receive training or compensation and is not expected to supervise medication doses. Patients are seen every week for the first month of HAART and then every 2–4 weeks. At each visit, patients are dispensed medications until their next appointment. Self-administration is the norm. Monthly laboratory monitoring for toxicity includes complete cell count and liver function tests. CD4 count and HIV load are performed every 6 months. Patients have access to psychiatric and psychological consultation, peer educators, and social work assistance. For patients lost to clinic follow-up, social workers may perform a home visit, if resources permit.

Data Collection and Measures

A separate, non-blinded team was trained to collect data using standardized forms from medical charts and patient interview. In addition to the variables described below, we collected sociodemographic and clinical characteristics, including TB status and treatment outcomes, baseline and follow-up weight, and substance use per physician assessment. We assessed depression, stigma, social support, quality of life and self-efficacy using standardized instruments that were administered in a one-on-one interview by a trained native Spanish speaker. We used the Hopkins Symptom Checklist to measure depression, the Berger Stigma Instrument, the Duke University of North Carolina Social Support Scale, and the Medical Outcomes Study HIV Quality of Life questionnaires (Berger et al. 2001; Broadhead et al. 1988; Derogatis et al. 1974; Wu et al. 1991). For self-efficacy, we used a scale derived by our sister organization, PACT, which was adapted from the HIV Self-Efficacy questionnaire (Shively et al. 2002), as well as the Confidence in Diabetes Self-Care Scale (Van Der Ven et al. 2003) and HIV self-management items specific to medication adherence developed and tested by Smith et al. (2003). The validation and internal reliability of these instruments in our cohort has been described elsewhere (Shin et al. 2008). We conducted interviews at baseline and 12 months and derived a change score (12 month score minus baseline score) for each scale.

We measured adherence as the number of days HAART was not taken over the total number of days in which HAART was prescribed within the last month of observation, based on patient self-report (Bangsberg et al. 2000). One of the most commonly used self-report tools was developed by the AIDS clinical trials group (ACTG) (Chesney et al. 2000). While the ACTG instrument measures adherence in the previous 4 days, recent data suggests greater intervention effect may be identified if adherence is measured over the past month (Simoni et al. 2006). We modified the ACTG to recall adherence over the past month. Individuals who were taking HAART were considered to have 0% adherence.

Clinical outcomes were virologic suppression; clinical status (on HAART, died, stopped HAART); TB treatment outcomes; and mean change in CD4 count at 12 months compared with baseline. Our primary endpoint, virologic suppression, was defined as having a viral load of <400 copies/ml at 1 year. As per intent to treat analysis, individuals who died or were missing viral load data were counted as unsuppressed.

Data Analysis

We provided baseline descriptions as proportions and means (with standard deviations, STD). To test significance, we reported the Chi-square for categorical variables, unless there were <5 predicted participants per cell where Fisher’s exact test was used. For continuous variables, we reported t tests or, for if not normally distributed, the Kruskal–Wallis test. We assessed the effect of our intervention on proportion with virologic suppression using univariate and multivariable analysis. For multivariable analysis, logistic regression analyses were performed on datasets multiply imputed using Markov Chain Monte Carlo methods (Schafer 1997). We included in this model all significantly different baseline characteristics between the intervention and control group as well as baseline characteristics associated with favorable response on univariate analysis. We assessed for effect modification of the two primary enrollment criteria (TB co-infection, female gender) upon the association of our intervention on outcome. We also excluded collinear variables, defined as those with a Pearson correlation coefficient of >0.60. We calculated post-hoc that our cohort size would enable us to detect a difference of 20% with a power of 80% and α = 0.05.

Results

As shown in Fig. 2, 95 adults were enrolled to receive CASA support. We matched 60 individuals to control subjects. These matched pairs (N = 120) comprise the cohort for analysis. Nine patients died before starting HAART. At 12 months of follow-up, 21 patients had died, and six abandoned HAART. None of the participants refused or quit the CASA intervention.

Fig. 2.

Intervention and control group flowchart

The CASA and control groups had some baseline differences, shown in Tables 1 and 2. Because the control region was somewhat less impoverished, the CASA group tended to have worse indicators of low socioeconomic status (food scarcity, lack of basic services, one-room households) and fewer had a history of substance abuse. Due to the time required to match and enroll controls, individuals in the intervention arm had a slightly longer time on HAART. Baseline CD4, viral load and weight did not differ significantly. Baseline psychosocial differences were notable for lower perceived HAART benefit among CASA participants.

Table 1.

Baseline sociodemographic and clinical characteristics (N = 120)

Variable N, if not 120	CASA cohort, N = 60 N (%) or Mean ± STDa	Control group, N = 60 N (%) or Mean ± STDa	X2, unless otherwise specified	P value	Degrees of freedom
Sex			0.00	1.00	1
Male	28 (46.7)	28 (46.7)
Female	32 (53.3)	32 (53.3)
Age	31.7 ± 7.8	31.9 ± 7.1	−0.16 (t test)	0.87	118
Civil status, 117			2.11	0.15	1
Married or living together	29 (48.3)	20 (35.1)
Single, separated, divorced, widowed	31 (51.7)	37 (64.9)
Socioeconomic status
Limited education,b 116	7 (11.9)	5 (8.8)	0.21 (Fisher’s exact)	0.76	1
Unemployed, 115	44 (75.9)	32 (56.1)	4.99	0.03*	1
Lacks basic services,c 119	20 (33.3)	7 (11.9)	7.82	0.005**	1
Food insecurity,d 106	34 (56.7)	16 (34.8)	5.00	0.03*	1
Difficulty accessing health services in past 3 months, 102	35 (62.5)	29 (63.0)	0.003	0.96
HIV status
Months from diagnosis to HAART,a 111	3.2 [1.6, 13.0]	3.3 [2.1, 11.1]	0.64 (Kruskal–Wallis)	0.43	1
Months on HAART at enrollmenta	1.3 [0.2, 3.9]	2.3 [0.0, 6.6]	3.27 (Kruskal–Wallis)	0.07	1
Weight (kg), 116	53.9 ± 10.0	53.4 ± 11.9	0.17 (t test)	0.86	93
CD4 (cells/ml3), 111	114.8 ± 87.2	109.7 ± 97.9	0.29 (t test)	0.77	109
Viral load (copies/ml),a 106	130,000 [29,000, 230,000]	72,000 [26,000, 284,000]	0.62 (Kruskal–Wallis)	0.43	1
Substance abuse (drug or alcohol)	12 (20.0)	24 (40.0)	5.71	0.02*	1
Documented drug abuse	3 (5.0)	10 (16.7)	0.03 (Fisher’s exact)	0.07	1
Documented alcohol abuse	11 (18.3)	22 (36.7)	5.06	0.02*	1
TB co-infection	33 (55.0)	35 (58.3)	0.14	0.71	1
Suspected MDR TB	8 (13.3)	8 (13.3)	0.00	1.00	1

^aIf non-normal, median [1st & 3rd quartiles]

^bIlliterate or no education beyond primary level

^cHome lacks at least one of the following: electricity, running water, or plumbing

^dPatient reported at least a day without food in the past 3 months due to poverty

^*P < .05

^**P < .01

Table 2.

Baseline psychosocial characteristics (N = 120)

Variable N, if not 120	CASA cohort, N = 60 N (%) or Mean ± STD	Control group, N = 60 N (%) or Mean ± STD	T-test, unless otherwise specified	P value	Degrees of freedom
Perceives HAART benefit, 102	44 (78.6)	44 (95.7)	0.01 (Fisher’s exact)	0.02*	1
Quality of life, 102
Quality of life	40.7 ± 9.1	40.0 ± 8.9	0.58	0.69	100
Physical health (PHS)	40.1 ± 10.0	40.8 ± 11.3	−0.11	0.77	100
Mental health (MHS)	41.3 ± 10.2	39.2 ± 9.8	1.17	0.30	100
Depression
HSC depression, 102	2.00 ± 0.55	1.96 ± 0.42	0.41	0.68	100
Suicidal ideation in past month, 102	14 (25.0)	9 (19.6)	0.43	0.51	1
Stigma score, 102	51.6 ± 14.4	46.0 ± 16.4	1.83	0.07	100
Social support, 102
Social support	62.3 ± 18.5	65.4 ± 20.7	−0.58	0.43	100
Emotional social support	69.4 ± 19.4	67.6 ± 21.4	0.60	0.65	100
Instrumental social support	51.6 ± 27.8	62.1 ± 30.7	−1.60	0.07	100
Self-efficacy
Self-efficacy	64.8 ± 19.3	66.0 ± 14.5	−0.37	0.71	100

^*P < .05

We evaluated psychosocial wellbeing among those who were on HAART at 12 months, shown in Table 3. The CASA group experienced significantly greater improvements in stigma (−10.4 vs. −1.7, t test (91, N = 93) = −2.70, P < 0.01), social support (+12.7 vs. −9.8, t test (91, N = 93) = 3.90, P < 0.01) and self-efficacy (+25.4 vs. +10.7, t test (91, N = 93) = 3.24, P < 0.01). Fewer CASA participants reported difficulty accessing health services (42.6% vs. 69.2%, Fisher’s (1, N = 93) = 7.37, P < 0.05). Both groups reported comparable improvements in quality of life and depressive symptoms, including a marked reduction in suicidal ideation. The control group reported almost minimal change in stigma and in fact reported decreased social support (in particular instrumental) compared with baseline. Clinical outcomes at 1 year are shown in Table 4. CASA participants were more likely to remain on HAART at 12 months (90.0% vs. 65.0%, Fisher’s (2, N = 120) = −0.0001, P < 0.01), be cured of TB (83.8% vs. 51.6%, Fisher’s (5, N = 120) = −0.0001, P < 0.05), and adhere to HAART (80.0% vs. 61.7%, X² (1, N = 120) = 4.88, P < 0.05). Mean adherence (with standard deviations) were 86.0% (STD 29.1) vs. 62.5% (STD 46.3), Kruskal–Wallis (1, N = 120) = 6.50, P < 0.05. Participants were more likely to have a suppressed viral load at 12 months if they received CASA support (76.7% vs. 58.3%, X² (1, N = 120) = 4.60, P < 0.05).

Table 3.

Psychosocial outcomes among those on HAART at 1 year (N = 93)

Variable	CASA cohort, N = 54 N (%) or Mean ± STD	Control group, N = 39 N (%) or Mean ± STD	T-test, unless otherwise specified	P value	Degrees of freedom
Health attitudes and behavior
Perceived HAART benefit	52 (96.3)	33 (84.6)	0.05 (Fisher’s exact)	0.06	1
Difficulty accessing health services	23 (42.6)	27 (69.2)	7.37	0.01**	1
Quality of life (QOL)
Change in total score	+14.8 ± 11.1	+11.5 ± 12.3	1.03	0.19	90
Change in physical QOL	+17.2 ± 11.8	+12.0 ± 14.1	1.58	0.06	90
Change in mental QOL	+12.2 ± 13.0	+10.9 ± 12.9	0.28	0.66	90
Depression
Change in depression	−0.42 ± 0.63	−0.21 ± 0.46	−1.68	0.07	91
Suicidal ideation in past month	4 (7.4)	3 (7.8)	0.31 (Fisher’s exact)	1.00	1
Stigma score
Change in stigma score	−10.4 ± 13.6	−1.7 ± 16.3	−2.70	0.005**	91
Social support
Change in social support	+12.7 ± 25.0	−9.8 ± 24.8	3.90	<0.0001**	91
Change in emotional social support	+4.0 ± 24.4	−6.4 ± 25.3	1.72	0.05*	91
Change in instrumental social support	+25.6 ± 35.6	−15.0 ± 33.3	5.10	<0.0001**	91
Self-efficacy
Change in self-efficacy	+25.4 ± 22.1	+10.7 ± 21.0	3.24	0.002**	91

^*P ≤ .05

^**P ≤ .01

Table 4.

Clinical outcomes at 1 year (N = 120)

Variable N, if not 120	CASA cohort, N = 60 N (%) or Mean ± STD	Control group, N = 60 N (%) or Mean ± STD	X2, unless otherwise specified	P value	Degrees of freedom
HAART status			−0.0001 (Fisher’s exact)	0.001**	2
On HAART	54 (90.0)	39 (65.0)
Abandoned HAART	0 (0)	6 (10.0)
Died	6 (10.0)	15 (25.0)
TB outcomes among TB patients, 68			−0.0001	0.02*	5
Cure	26 (83.8)	17 (51.6)
Treatment completed	0 (0.0)	2 (6.5)
Failure	3 (9.7)	4 (12.9)
Death	1 (3.3)	7 (22.6)
Default	0 (0.0)	2 (6.5)
In treatment	1 (3.2)	0 (0)
CD4 cell count, 89	269.7 ± 115.0	264.0 ± 161.0	0.06	0.87	87
Change CD4 cell count, 89	143.5 ± 120.9	148.9 ± 129.6	−0.34	0.84	87
HAART adherence (≥95% doses in past month)	48 (80)	37 (61.7)	4.88	0.03*	1

^*P < .05

^**P < .01

We performed univariate analysis to identify factors associated with achieving virologic suppression at 12 months, shown in Table 5. Self-efficacy was associated with greater chance of achieving virologic suppression. For logistic regression analysis, we controlled for baseline differences in the control and intervention groups (unemployment, lacking basic services, food scarcity, substance abuse, and perceived benefit of HAART), in addition to self-efficacy. None of the covariates in the model were collinear and we detected no effect modification. CASA support was associated with a 2.75-fold increased chance of achieving a suppressed viral load at 1 year (adjusted OR and 95% CI: 2.75, 1.03–7.33, degrees of freedom = 7). The only other factor significantly associated with 12 month outcome was food scarcity (adjusted odds ratio 0.25, 95% CI 0.19, 0.61, degrees of freedom = 7).

Table 5.

Baseline characteristics associated with suppressed viral load at 12 months on univariate analysis (N = 113)

Variable	Suppressed viral load, N = 76 N (%)/Mean ± STD	Death or unsuppressed viral load, N = 44 N (%)/Mean ± STD	X2, unless otherwise specified	P value	Degrees of freedom
Male gender	37 (45.7)	19 (48.7)	0.10	0.75	1
Age	31.7 ± 7.9	32.0 ± 6.4		0.81
Unemployed	53 (66.3)	23 (65.7)	0.003	0.96	1
Lacks basic services	19 (23.5)	8 (21.1)	0.09	0.77	1
Food insecurity	35 (43.2)	15 (60.0)	2.16	0.14	1
Substance abuse	21 (25.9)	15 (38.5)	1.97	0.16	1
TB co-infection	43 (53.1)	25 (64.1)	1.30	0.25	1
Perceives HAART benefit at baseline	70 (86.4)	18 (85.7)	0.27 (Fisher’s exact)	1.00
Difficulty accessing health services	52 (64.2)	12 (57.1)	0.36	0.55	1
Depression	1.96 ± 0.53	2.05 ± 0.32	−1.01	0.44	52
Stigma	48.5 ± 15.5	51.4 ± 15.7	−0.78	0.32	100
Social support	65.2 ± 19.6	57.9 ± 18.3	1.53	0.13	100
Self-efficacy	67.6 ± 20.5	56.7 ± 20.2	2.65	0.009**	100
CD4 ≤ 200	64 (79.0)	25 (83.3)	0.19 (Fisher’s exact)	0.79	1

^**P < .01

Discussion

This pilot experience suggests that comprehensive community-based accompaniment with DOT-HAART may be instrumental in improving clinical and psychosocial outcomes within the first year of antiretroviral therapy. We observed a significant association between the intervention and suppressed viral load at 12 months. Our data add to the scant literature of controlled studies of community-based DOT-HAART in resource-poor settings. Idoko et al. (2007) compared daily and modified DOT by community and family members with self-administration and observed greater rates of virologic suppression at 48 weeks. In a recent RCT providing modified DOT-HAART (m-DOT-HAART) in Kenya, Sarna et al. (2008) observed short-term benefits on adherence in the entire cohort, and a significant long-term effect of m-DOT-HAART on virologic suppression among individuals suffering from depression. Pearson et al. (2007) conducted an RCT of m-DOT-HAART in Mozambique and observed improved rates of adherence at 6 and 12 months. Although viral load was not assessed, mean CD4 cell count did not differ significantly at both study endpoints. Compared with these studies, we may have observed greater impact because of the community-based long-term nature of our intervention, as both of these studies required patients to attend health centers daily to receive m-DOT-HAART and their interventions lasted between 6 and 24 weeks. However, perhaps more importantly, our outcomes were assessed just as individuals were completing DOT-HAART and do not reflect the durability of the intervention, unlike data reported by Sarna et al. (2008) and Pearson et al. (2007). We hope that additional outcomes assessments of our cohort at 24 months, i.e., 12 months after DOT-HAART, will be informative.

To our knowledge, our study is the first quantitative assessment of the psychosocial impact of community-based DOT-HAART. Several studies support the importance of psychosocial support provided by DOT-HAART. Nachega et al. (2006) have eloquently described the impact of patient-selected treatment supporters, identifying the importance of trust, emotional support and instrumental support provided by supporters and other family members. Bradley-Ewing et al. (2008) have also described the psychosocial benefits among m-DOT-HAART participants in an ongoing US-based trial. Modified DOT-HAART participants described greater motivation to adhere to HAART and other medications, strengthened ability to communicate with providers, and improved overall quality of life, in part through decreased loneliness and hopelessness, and better mood. These data support our own findings that community-based accompaniment has an important impact beyond direct medication supervision. Among these, our findings rebut concerns that community-based accompaniment may not be acceptable to HIV-positive individuals due to stigma concerns. Similar to our Haiti experience (Castro and Farmer 2005), we have found that CASA support does not increase but rather reduces stigma, through the act of receiving emotional support from a community peer, which in turn, cultivates behavior changes among family members and providers. Further, the improvements in psychosocial indicators in our cohort at 12 months support a possible mediating mechanism by which CASA support could achieve long-term HAART adherence: that of increased social support, which in turn decreases perceived stigma and bolsters self-efficacy.

Interestingly, the control group also experienced dynamic changes in psychosocial status during the first year of HAART. Depression, suicidal ideation, and quality of life improved by surviving the first year of HAART; on the other hand, individuals in the control group reported less social support (in particular instrumental support) at 1 year. We have frequently observed the tendency for family members to withdraw support once the patient is no longer critically ill, as limited emotional and material resources are exhausted over time.

We also found that food insecurity was associated with failure to achieve virologic control at 12 months. Food insecurity is known to impact HIV outcomes in numerous ways. HIV-positive individuals with competing priorities of poverty and hunger are less likely to utilize health services and adhere to antiretroviral therapy (Hardon et al. 2007; Nachega et al. 2006). Malnutrition and micronutrient deficiencies increase vertical transmission, accelerate HIV progression and increase mortality among HIV-positive individuals (Semba et al. 1995). Conversely, physical illness and decreased productivity from HIV/AIDS further feeds the cycle of economic stress and food insecurity (Bukusuba et al. 2007; Kadiyala and Gillespie 2004). Given the profound impact of poverty and food insecurity on HIV outcomes, we have argued that adherence interventions for HIV-positive individuals in resource-poor settings must address economic instability and food insecurity in order to achieve long-term success.

Our study is limited in its small size and differences between intervention and control groups. Because this study is not randomized, there may be additional confounders that have not been taken into account and bias study results. Further, we prioritized TB co-infected and female patients, in response to the community’s perception of greatest need. That the outcomes of our control group are worse than the outcomes of the general cohort of HIV-positive patients treated at the control hospital demonstrate that we have indeed identified vulnerable groups at risk of doing poorly during the first year of HAART. While this limits the generalizability of our findings, we did not detect effect modification by either primary enrollment category. Based on our understanding of the HIV-affected population in Peru and elsewhere, we feel that this cohort likely represents the most vulnerable groups who may most benefit from comprehensive accompaniment. TB patients and women with HIV/AIDS are not only among the most socioeconomically marginalized individuals in Peruvian society; further, they are groups that must often negotiate between multiple “vertical” health systems (e.g., TB and obstetrics in addition to HIV programs) and often fall through the cracks of coordinated care.

Conclusions

Despite its limitations, this pilot experience invites further exploration of CASA support and its potential impact on early and long-term physical and psychosocial recovery of individuals starting HAART in resource-poor settings. Long-term follow-up data as well as an assessment of cost and health service utilization are needed to fully understand the effectiveness of CASA in addition to matched support.