metadata: authors: 0: author: Booysen,Frederik Le Roux
1: author: De Walque,Damien B. C. M.
2: author: Over,Mead
3: author: Hashimoto,Satoko
4: author: de Reuck,Chantell
count: South Africa
docna: 0: docna: A randomized control trial of a peer
            adherence and nutritional support program for public sector
            antiretroviral patients
docty: Policy Research Working Paper
subtopic: Pharmaceuticals Industry,Health Care Services Industry,Pharmaceuticals & Pharmacoeconomics,Educational Sciences,HIV AIDS,Cholera,Communicable Diseases,Leprosy
teratopic: Health, Nutrition and Population
abstracts: cdata!: Access to antiretroviral treatment has
            expanded rapidly in South Africa, making it the country in
            the world with the largest treatment program. As
            antiretroviral treatment coverage continues to rise in
            resource-constrained settings, effective community-based
            adherence support interventions are of central importance in
            ensuring the long-term sustainability of treatment. This
            paper reports the findings from a randomized control trial
            of a peer adherence and nutritional support program
            implemented in a public health care setting in South
            Africa's antiretroviral treatment program. The analysis
            assesses the impact of these peer adherence and nutritional
            support interventions on self-reported adherence, timeliness
            of clinic and hospital visits, and immunologic response to
            antiretroviral treatment. Peer adherence and nutritional
            support improved the timeliness of adults´ clinic and
            hospital visits for routine follow-up while on
            antiretroviral treatment. Peer adherence support impacted
            positively on immunologic response to antiretroviral
            treatment. Scale-up of effective and sustainable
            community-based, peer-driven adherence and nutritional
            support interventions should form part of the United Nations
            AIDS Treatment 2.0 strategy's community mobilization
            and health system strengthening pillar.
geo_reg_key: 517195,517191
repnme: repnme: A randomized control trial of a peer
            adherence and nutritional support program for public sector
            antiretroviral patients
display_title: A randomized control trial of a peer
            adherence and nutritional support program for public sector
            antiretroviral patients
listing_relative_url: /research/2016/07/26589283/randomized-control-trial-peer-adherence-nutritional-support-program-public-sector-antiretroviral-patients
topicv3: Education m1327048 470,HIV/AIDS m1327522 1416,Pharmaceuticals m1327740 1350,Health m1504661 3480,AIDS Treatment m1504737 3529
publishtoextweb_dt: 2016-07-21T00:00:00Z
historic_topic: Health, Nutrition and Population
no_of_pages: 37
author_keys: 0: author_key: 763358
1: author_key: 687876
2: author_key: 1127417
model_extractions: WPS7760 Policy Research Working Paper 7760 A Randomized Control Trial of a Peer Adherence and Nutritional Support Program for Public Sector Antiretroviral Patients _Frederik Booysen Damien de Walque Mead Over Satoko Hashimoto Chantell de Reuck_ Development Research Group Human Development and Public Services Team July 2016
Policy Research Working Paper 7760

# **Abstract**

Access to antiretroviral treatment has expanded rapidly in South Africa, making it the country in the world with the largest treatment program. As antiretroviral treatment coverage continues to rise in resource-constrained settings, effective community-based adherence support interventions are of central importance in ensuring the long-term sustainability of treatment. This paper reports the findings from a randomized control trial of a peer adherence and nutritional support program implemented in a public health care setting in South Africa’s antiretroviral treatment program. The analysis assesses the impact of these peer adherence and nutritional support interventions on self-reported adherence, timeliness of clinic and hospital visits, and immunologic response to antiretroviral treatment. Peer adherence and nutritional support improved the timeliness of adults ́ clinic and hospital visits for routine follow-up while on antiretroviral treatment. Peer adherence support impacted positively on immunologic response to antiretroviral treatment. Scale-up of effective and sustainable community-based, peer-driven adherence and nutritional support interventions should form part of the United Nations AIDS Treatment 2.0 strategy’s community mobilization and health system strengthening pillar.

This paper is a product of the Human Development and Public Services Team, Development Research Group. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at booysenfrikkie@gmail.com and ddewalque@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# **A Randomized Control Trial of a Peer Adherence and Nutritional Support Program for Public Sector Antiretroviral Patients**

Frederik Booysen (University of the Free State, South Africa) Damien de Walque (The World Bank) Mead Over (Center for Global Development) Satoko Hashimoto (The World Bank) Chantell de Reuck (University of the Free State, South Africa).

## JEL Codes: I15, O12, O15.

## Keywords: HIV and AIDS, Health, Nutritional Programs.

**_Acknowledgements_ :** We thank the study participants and the fieldwork staff as well as the Free State Department of Health (FSDOH) and National Health Laboratory Service (NHLS). The study was funded by the following institutions: Research Committee of the World Bank; The Bank Netherlands Program Partnership; WB-DfiD ‘Evaluation of the Community Response to HIV and AIDS’; Program to Support Pro-Poor Policy Development (PSPPD); a partnership between the Presidency, Republic of South Africa and the European Union; Health Economics and Aids Research Division (HEARD) at the University of Kwazulu-Natal; University of the Free State (UFS); and South Africa’s National Research Foundation (NRF).
# **1. Introduction**

In view of the reduction in the cost of triple-drug therapy and the accumulating evidence of the feasibility and effectiveness of ART in slowing the progression of AIDS in poor countries (Havlir, 1998, Lange et al, 2004; Zewdie, Lange and Kuritzkes, 2004), the South African government in 2003 announced a “roll-out” plan for antiretroviral treatment (ART) via the public health sector. South Africa faces the largest HIV burden in the world and currently has the largest ARV treatment program in the world. At present, the program provides treatment to three million people living with HIV and AIDS (PLWHA) (Nene, 2015).

The potential benefits of ARV treatment to the individual patient are enormous (Lange et al, 2004; Sterne, et al, 2005) and improvements in the health status of infected individuals are likely to benefit their families’ and their children’s well-being (Bhargava, 2005). The patient’s better health will enable him or her to contribute more to household production and wage-earning activity and to enjoy more leisure activities and a healthy life. As a consequence of the patient’s health, other household members whose time would have gone to care for the AIDS patient or to substitute for the patient’s work can instead pursue higher gain activities, including schooling for the children, labor market participation for adults and leisure activities. However, in order to ensure that these benefits are realized, adherence to ARV treatment must be strict (Nachega et al, 2010). As ART is extended to populations far larger than have ever been reached by ARV treatment programs in developed countries, adherence is likely to suffer and information on the socioeconomic and policy determinants of adherence in poor countries will be increasingly needed. The UNAIDS Treatment 2.0 strategy, moreover, envisages an expanded role for the mobilization of communities in treatment programs (pillar 5), including the use of lay health workers or treatment supporters to provide adherence support to ART patients (UNAIDS, 2011), which furthermore may impact on two other pillars of the Treatment 2.0 strategy, namely reduction in costs and the strengthening of delivery systems (Torpey et al., 2008).

Research synthesis of empirical studies on ARV adherence however paints a relatively gloomy picture. An early synthesis of the effects of adherence interventions for ART concludes that more widely targeted interventions have relatively small effects, while only interventions targeting 2
patients with known or anticipated adherence problems show medium effects (Amico et al., 2006). A more recently completed systematic review, which compares the adherence benefits of directly observed versus self-administered ARV treatment moreover finds that directly observed therapy does not outperform self-administered treatment on viral suppression and a range of other adherence measures (Ford et al., 2009), thus bearing out Liechty and Bangsberg’s (2003) pessimism regarding the benefits of directly observed therapy programs for ARV treatment. Yet, another systematic review, which expands study selection criteria to include nonrandomized study designs, claims that directly observed therapy does outperform self-administered treatment on adherence, immunologic and virologic outcomes (Hart et al., 2010). Two recently published studies not included in the former syntheses in turn do report statistically significant, positive impacts on adherence of directly observed therapy interventions (Babudieri et al., 2011; Berg et al., 2011), the latter of which employs a randomized study design. To date, therefore, there appears to be no consensus that community-based adherence support provided through the likes of lay workers impacts positively on adherence and clinical response to ARV treatment.

This paper employs longitudinal, panel data from the Effective Aids Treatment and Support in the Free State (FEATS) study to determine how a randomized peer-adherence and nutritional support intervention impact on various subjective and more objective measures of ARV treatment adherence. Section 2 describes the study design and data, while section 3 summarizes the methods employed in the statistical and econometric analyses. Section 4 presents the results, while section 5 concludes.

# **2. Methodology**

The Effective Aids Treatment and Support in the Free State (FEATS) study, a prospective cohort study and experimental study with a combined group time-series, quasi- or field experiment and Zelen-type double randomized consent design,<sup>1</sup> was approved by the Ethics committee of the Faculty of Health Sciences (UFS) [ETOVS 145/07]. The experimental component of the FEATS

> 1 In the Zelen design subjects are only offered and provided with information regarding the treatment that they are assigned. The Zelen design is deemed appropriate given the fact that: blinding is not practicable or possible; the use of classical randomization and informed consent procedures significantly threatens internal validity; the interventions are highly attractive; the control group receives standard care; the study focuses on a clinically relevant objective(s) and offers important new insights (Kaptchuk, 2001; MacLehose _et al_ , 2001; Rains & Penzien, 2005).

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study comprised a peer adherence and nutritional support intervention. The trial is registered in South Africa [DOH-27-0907-2025] and with the United States’ National Institutes of Health (NHI) [NCT00821366].

# **2.1 Experiment**

The open enrollment into this prospective, experimental study was managed by ARV nurses employed at each of the 12 larger phase-I ART clinics in Free State province. Eligible ARV clients had to be adult (18+ years), had to have initiated ART in the past month, and had to reside in the local community where the particular clinic is based. ARV patient and patient households recruited into the study were randomly assigned to one of three groups: a control group receiving treatment and support provided in the existing program, a group that received bi-weekly visits by trained peer adherence supporters (PAS) and a group that received the bi weekly visits by the PAS adherence supporters and nutritional supplements (refer Figure 4). The nutritional support consisted of two 400g cans of meatballs and spaghetti in tomato sauce per week. Each can contains (per 100 grams) 420 kJ of energy, 6.6 grams of protein, 9.9 grams of carbohydrates, 4.1 grams of fat, 29.9 mg of magnesium, 116.6 mg of phosphorous, and 1.6 mg of iron. In addition, the tomatoes are a good source of vitamin C.

Prior to follow-up, the peer adherence and nutritional interventions were implemented. Approximately 60 peer adherence supporters were recruited in consultation with ART staff at the relevant clinic, in proportion to the number of FEATS study participants recruited at each facility. To be considered, individuals had to have been on ARV treatment for ≥ 12 months, had at least a grade-10 certificate, and live within walking distance from the relevant clinic. Peer adherence reporters received 5-days of basic training in ART and adherence support from staff at the School of Nursing at the University of the Free State. Training focused on seven main themes: facts about HIV/AIDS, anti-retroviral therapy (ART), adherence supported needed by an ART client, nutrition, infection control at home, and using a health care team approach. On the 5<sup>th</sup> day of training, peer adherence supporters’ knowledge and practical skills was assessed by the trainers using an oral test and practical exercise.

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Following the completion of training and assessment, peer adherence supporters were assigned eight FEATS study participants each, four in each intervention arm. An original randomization list was employed for this purpose, with an additional, rank-ordered list of reserve cases, per intervention group. During recruitment, PAS explained the intervention to each client and obtained written, informed consent from FEATS study participants who volunteered to partake in the experiment. As illustrated in Figure 5, a relatively large proportion of patients randomized to the two treatment arms of the study (almost one-third) could not be traced and contacted to be offered the relevant intervention. As a result, one in four study participants recruited into the two experiments represented so-called reserve cases originally included in the control group. A small proportion only (6.1% or 22 cases) of contacted study participants refused the offered adherence and nutritional support, while due to logistical issues a small number of participants assigned to a treatment crossed over to the other treatment arm at implementation (13 cases or 3.9%). (For a detailed discussion of Figure 5 refer to the CONSORT statement.) During the study, a brief survey instrument was used to collect key information from the 52 peer adherence supporters (PAS) working in the project at the time. (Initially, a total of 57 peer adherence supporters was recruited, trained and employed. By this time, five PAS had resigned due to not being able to fulfil their responsibilities, with patients being re-assigned to other PAS.) The peer adherence supporters can be described as follows:

- Predominantly female (98%) – only one male PAS remains in the study

- Mainly holds higher secondary education levels: grade 10 (20%), 11 (34%), 12 (38%)

- Aged mid to higher 30’s: mean age 35.8 years, [median 34.5 years, IQR 32.0 – 39.5]

- Majority walk when visiting clients: 56% walk, 38% taxi/bus, 6% own transport

- Single trip to closest client on average takes 39.1 minutes [median 30 min, IQR 15–60]

- Single trip to furthest client on average takes 94.5 minutes [median 90 min, IQR 45–120]

- Majority (98%) meets their client at the client’s home

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By completion of the experiment, the majority of PAS (55.6%) had already been on ARV treatment for 5 years.

During the experimental phase of the study, these peer adherence supporters visited each client at least twice per week. At each visit, the peer adherence supporter had to complete a one-page check list. Peer adherence supporters were paid a monthly stipend of $100 (ZAR 800), conditional on performance. Supervision was performed by two trained peer adherence support coordinators, whom visited each clinic once a month to meet with the relevant peer adherence supporters. During this visit, peer adherence supporters received re-training on selected topics included in the original main training to refresh and maintain knowledge transfer. In addition, supervisors debriefed PAS, dealt with any logistic problems and collected completed checklists from PAS. Supervisors completed a standard, short-report for each site visit. Following each monthly visit, supervisors met with the PAS coordinator at the Faculty of Medicine, who collated information from their reports and further discussions into a monthly progress report. Information in the monthly report was used to determine PAS payments for the subsequent month. For the study participants allocated to group C, the PAS were in addition delivering two cans of the food support at each visit.

By completion of the FEATS intervention at 18-months, a substantial proportion of FEATS study participants (39.8%) had dropped out of the treatment arms, probably due to a combination of fatigue among both participants and peer adherence supporters as well as the potential discontinuation of support in anticipation of the completion of the study. On aggregate, patients spent 13.8 months on the FEATS treatment. Patients in the peer adherence support only arm on average were in the intervention for longer that patients in the adherence and nutritional support arm (14.4 versus 13.1 months), a difference that is statistically significantly different (p=0.011). Figure 6 shows the survival functions for each of the two treatment arms. However, the difference in the survival functions, according to the log-rank test for equality of survivor functions, is not statistically significantly different (p=0.227). At the completion of the intervention, study participants were debriefed and asked to sign a formal termination of experimental intervention notice. ARV patients in the control group were provided with two month’s stock of the canned 6
food that the peer adherence and nutritional support intervention group received for the duration of the experimental intervention.

In the subsequent pages, patient-level data are used to investigate the impact of peer adherence and nutritional support on measures of ARV treatment adherence and success.

# **2.2 Data collection**

Trained enumerators conducted structured, face-to-face baseline interviews with ART patients recruited into the study.<sup>2</sup> Written, informed consent was obtained from study participants by the nursing personnel at the respective clinics (for ARV patients), as well as by the enumerator (for ARV patients and ARV patient/comparison households). A facility survey was also conducted, during which semi-structured interviews were conducted with health care providers at each study site.

At follow-up, enumerators again obtained written, informed consent from study participants. Two rounds of follow-up interviews were conducted with patients. The median time between consecutive interviews was 11.7 months [IQR 10.6-15.9 months]. A total of 1,588 interviews were conducted with 653 individual patients, 422 of whom were interviewed at both follow-ups. By the second and final round of follow-up interviews, 218 patients had been lost to follow-up, primarily due to mortality among study participants (42.4%) and unknown whereabouts (34.1%), which translates into an aggregate attrition rate of 33.6%. Of the 337 patients that consented to enrollment in the adherence and nutritional support interventions at the commencement of the intervention, 288 or 85.4% were interviewed at the first round of follow-up interview, whereas 175 or 86.2% of the 203 study participants that completed the full 18-months of FEATS treatment were interviewed at the second and final round of follow-up interviews.

On completion of the study clinical bio-markers and other additional patient information were obtained from paper and electronic files. Patients at baseline, when first recruited into the study,

> 2 The study also included a household survey component, with interviews being conducted with patient and comparison households, this to achieve various other objectives of the larger study (refer CONSORT statement).

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consented that the research team access their clinic and hospital records to collect the latter information.

# **2.3 Socio-demographic and other characteristics of the study population**

Table 1 reports selected baseline characteristics of the FEATS patient study population. Study participants were mostly in their late 30s. As is the case in the ARV program in general, approximately three in four study participants were women. Two-thirds of patients enrolled into the FEATS study were single, while one in four lived with their partner or spouse. Three-quarters lived in formal dwellings and one in five in informal dwellings. Only in one in five participants had completed secondary school or held some tertiary education, while almost half had some level of secondary education [grade 8-11]. Households generally included 2-4 members, one in three of which represented a child or elderly person. With the exception of age (attrited study participants were marginally, but statistically significantly younger than study participants interviewed in both rounds of follow-up interviews), socio-demographics did not differ statistically significantly across FEATS study participants that stayed in the study and those that were lost to follow-up, thus suggesting the absence of major attrition bias.

# **3. Methods**

Adherence outcomes for study participants were measured as follows: a continuous and dichotomous version of the CASE index of self-reported adherence (Mannheimer et al.. 2006); a continuous, normalized index of self-reported adherence derived from five categorical variables on self-reported adherence using multiple correspondence analysis (MCA adherence index); a selfreported, dichotomous 0/1 variable for a missed clinic or hospital visit; and timeliness for scheduled clinic and hospital visits, which represents a more objective proxy of adherence than self-reported adherence (Blacher et al., 2010; Kunutsor et al., 2010). Delays in clinic and hospital visits, used here to measure timeliness of visits, were calculated by subtracting the scheduled visit dates from the actual visit dates for consecutive clinic and hospital visits. The latter variable was also converted into a dichotomous variable indicating whether the patient arrived three or more days late for the particular visit (=1) or not (=0). Immunologic response to ARV treatment is measured using CD4 counts (cells per microliter). (In the case of timeliness of clinic and hospital 8
visits and CD4 counts, the data includes all outcomes observed between recruitment into the study and completion of the FEATS experiment. The advantage of the latter approach is that the statistical power of the analysis increases dramatically, because observations included in the analysis originates from patients’ records and is therefore not dependent on a patient interview having been conducted with the said FEATS study participant.) The analysis conducted in this study comprised the following: _Firstly_ , we assess balance at baseline in adherence outcomes and other observable socio-demographic characteristics, by original intent-to-treat status and actual treatment arms (Tables 2-5). On the basis of this evidence, we reflect on the presence of potential selection bias. _Secondly_ , we employ basic bivariate analysis to assess differences in our main outcomes, i.e. self-reported adherence outcome, timeliness of clinic and hospital visits, and immunologic response, across treatment arms for intent-to-treat and actual treatment status (Tables 6-7; Figure 7-8). The statistical significance of differences in means and medians are assessed using t-tests, F-tests and Wilcoxon rank-sum tests. _Finally_ , we employ fixed effects (FE) linear regression models with Instrumental Variables (IV) and random effects (RE) linear regression models adjusted for selection bias to investigate the impact of the FEATS experiments on self-reported adherence, timeliness of clinic and hospital visits, and immunologic response to ARV treatment (Tables 8-10; Figure 9). In each case, we control for basic sociodemographics and ARV treatment duration. Following suggestions by Angrist et al (1996) and Greenland (2000), the original intent-to-treat status is used as instrument to adjust for selection bias in the fixed effects (FE) regression analysis, while in the random effects (RE) regression analysis the inverse Mills ratio is used to adjust for selection bias. To be deemed significant for the purposes of discussion, results need to be statistically significant at least at the 95% level (although results significant at a 90% level are reported).

# **4. Results**

At baseline, age, sex, education, monthly income and pre-ART CD4 count, in terms of the intentto-treat comparison, did not differ significantly across treatment arms, as did all self-reported measures of adherence. However, differences in marital status are statistically significant when comparing the peer adherence support only and control groups. The peer adherence support only arm comprise a larger proportion of single adults compared to the control group.

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Timeliness of clinic and hospital visits at baseline does though differ statistically significantly across treatment arms. Delays in clinic and hospital visits for clients in the two treatment arms exceeded delays for the control group. More specifically, delays in clinic visits were significantly lower in the peer adherence support only arm, and delays in hospital visits significantly lower in the peer adherence and nutritional support arm. These differences possibly are the result of patient files not being available for data extraction for all study participants, which implies that outcomes are not missing in a non-random manner. Yet, balance does exist across treatment arms in selfreported adherence and most observable socio-demographic characteristics.

Tables 4-5, however, illustrate the presence of a clear selection bias into the treatment arms of the experiment. In the case of the arm for peer adherence support only, those with higher levels of education selected into treatment. According to our results, study participants who exhibited poorer adherence than those in the control group in terms of record-based timeliness of clinic and hospital visits selected themselves into the peer adherence and nutritional support interventions. The opposite, however, is true for self-reports of missed clinic and/or hospital visits. Here, those selecting into the peer adherence support only arm, reported better adherence than in the control group. (As the former are considered more objective measures of adherence, we discount the latter evidence of selection bias in favor of the former.) For these reasons, regression results were adjusted for selection bias using instrumental variables (IV).

Moving to study outcomes as observed before and during the provision of peer adherence and nutritional support, there are few significant differences in adherence outcomes by the intent-totreat assignment of subjects. Only in the case of the proportion of delayed clinic visits is the outcome significantly better in the two treatment arms as well as in the combined treatment arm for any peer adherence support. The same is true for comparisons based on actual treatment assignment, including for the duration of delays in clinic visits (see Figures 7a/b). This is not true for hospital visits (Figures 8a/b).

The attention now shifts to the results of the regression analysis. Table 8 provides little evidence that the experiment’s interventions impacted significantly on measures of self-reported adherence. (Two of the three results significant at the 10% level are counter-intuitive (support increases the reporting of missed clinic and/or hospital visits), whereas one result only supports the argument 10
that peer adherence and nutritional support results in fewer missed visits for routine medical checkups.) No results are statistically significant at the 5% level.

Table 9 reports the results for the intent-to-treat and the Fixed Effects (FE) with instrumental variables (IV) regression analysis of timeliness of clinic and hospital visits. There is strong evidence that the combination of peer adherence and nutritional support impacts positively on adherence. Clients receiving peer adherence and nutritional support are less likely to miss clinic and hospital visits and less late for hospital visits, regardless of whether the analysis is based on intent-to-treat assignment or actual treatment assignment, correcting for selection. The results hold in part when the analysis focuses on the combined treatment arms (i.e. any peer adherence support), particularly for missing a clinic visit.

Table 10 suggests that peer adherence support only impact positively on CD4 counts. Estimates show that a person in the peer adherence support only group will have a CD4 count that is permanently larger by 60 cells per microliter. According to simulations based on the coefficients in table 4, a person receiving peer adherence support only will have a CD4 count 12 points higher after 1 month, 24 points higher after 4 months, 50 points higher after 16 months, and 60 points higher after 25 months. These significant improvements in CD4 counts are maintained across the duration of the peer adherence support intervention, regardless of whether adherence support commences at 6, 12 or 18 months on ARV treatment (Figure 9).

The result that nutritional support (in combination with peer adherence support) does not impact on clinical outcomes is perhaps not surprising, given the relatively small size of the supplement (2 cans of food per week) and the fact that the vast majority of clients (>95%) reported sharing the food with others. It is also likely that patients took up the combined treatment, not because of a need for peer adherence support, but due to the opportunity of receiving nutritional support that helps strengthen the household’s food security.

It is also interesting here that the impacts of treatment on behavioral as opposed to biomedical outcomes are different: peer adherence and nutritional support impact on timeliness of visits, while peer adherence support only impacts on immunologic response. Further research is required to untangle the behavioral complexities underlying such results.

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# **5. Conclusion**

The quantitative findings presented in this paper suggest that peer adherence and nutritional support, though not impacting significantly on self-reported adherence, do improve the timeliness of adults ́ clinic and hospital visits. In addition, adherence support has been shown to impact positively on immunologic response to ART treatment. These results suggest that scaled-up effective and sustainable community-based, peer-driven adherence and nutritional support interventions would be a useful component of the UNAIDS Treatment 2.0 strategy ́s community mobilization and health systems strengthening pillars.

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Santos, C., Adeyemi, O. & Tenorio, A., 2006. Attitudes towards directly administered antiretroviral therapy (DAART) among HIV-positive inpatients in an inner-city public hospital. _AIDS Care_ , 18(7): 808811.

Shin, S., Munoz, M., Zeladita, J., Slavin, S., Caldas, A., Sanchez, E., Callacna, M., Rojas, C., Arevalo, J., Sebastian, J.L. & Bayona, J., 2011. How does directly observed therapy work? The mechanisms and impact of a comprehensive directly observed therapy intervention of highly active antiretroviral therapy in Peru. _Health and Social Care in the Community_ , 19(3): 261-271.

Sterne J.A.C., Hernán M., Ledergerber B., Tilling K., Weber R., Sendi P., Rickenbach M., Robins J., Egger M. & Swiss HIV Cohort Study. (2005). Long-term effectiveness of potent antiretroviral therapy in preventing AIDS and death: a prospective cohort study. _Lancet_ , 366, 378–84.

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UNAIDS. 2011. _The Treatment 2.0 Framework for Action: Catalysing the Next Phase of Treatment, Care and Support_ . Geneva: UNAIDS.

Zewdie D., Lange J. & Kuritzkes D., 2004. Editorial. _AIDS_ , 18 (Supplement 3): S1-S3.

15
<!-- Start of picture text --> Optimize drug<br>regimes<br><!-- End of picture text --> <!-- Start of picture text --> Mobilize Provide<br>communities point of care<br>diagnostics<br><!-- End of picture text --> <!-- Start of picture text --> Strengthen delivery Reduce costs<br>systems<br><!-- End of picture text -->
<!-- Start of picture text --> ART Adherence Effect Sizes<br>2 Al 0 1 2 3<br>Anonymous, 1999 [51] rr rs a es<br>Dilorio ct al., 2003 [52] i<br>Fairleyct al., 2003 [53]<br>Goujard et al., 2003 [54] (Personalized)<br>Goujard ct al., 2003 [54] (Personalized plus education)<br><!-- End of picture text -->

|ART<sup>Adherence</sup><br>Effect Sizes|
|---|
|2<br>Al<br>0<br>1<br>2<br>3<br> <br><br>|
|Anonymous, 1999[51]rr<br>rs a<br>es<br><br>|
|Dilorio ct al., 2003 [52]<br>i<br>|
|Fairley<br>ct al., 2003 [53]<br>Goujardet al., 2003 [54](Personalized)<br>Goujardct al.,2003 [54] (Personalized pluseducation)<br>|
|Haubrich<br>et al.,1998 [32]<br>Holzemeretal.,2000[55]<br>:|
|<br><br>ina0.<br>|<br>—<br>|<br>|<br>Malowetal,1998[57]<br>[++|
|<br><br><br><br><br> <br><br>Mannctal.,2001[59]}<br>H<br>‘<br>i<br>i<br>:<br> <br><br>|
|<br><br><br><br><br><br> <br><br>|
|<br><br><br>McPhersoo-Baker ct al., 300) [27]<br>‘<br>|
|Molassiotisetal,,2003[59]<br><br>|
|<br><br>|
|Powell-Copeetal.,2003[28]<br>:<br> <br><br><br><br><br>|
|<br><br>Pradier<br>ot al, 2003 [62]<br>|<br>i<br>Lie<br>|<br>i<br><br>|
|Rigsby et al., 2000 [29] (Cue-dosing)<br>:|
|Rigsbyetal.,2000[29](Cue-dosingplus cashreinforcement)<br>|<br>Safren<br>c**ta**l**,200**1**[6**3**]**<br>Safren<br><br><br><br>|
|<br><br> <br> e<br>l.<br>3<br>4<br>a|
|Stenzelet al., 2001 [66]<br>;_—<br> <br><br><br>|
|Tesoriero<br> <br><br><br><br>|
|<br><br><br> et<br>, 20 0 31|
|2<br>4<br>0<br>1<br>2<br>3<br>|
|FffectSize|

<!-- Start of picture text --> Holzemer et al., 2000 [55] :<br>Malowina et al, 19980. [57] | [++— | |<br>Mann ct al., 2001 [59] } H ‘ i i :<br>Margolin et al., 2003 [30] t+ |<br>McPhersoo-Baker ct al., 300) [27] ‘<br><!-- End of picture text -->

<!-- Start of picture text --> Powell-Copesere,et al., 2003 [28] SS:<br>Pradierot al, 2003 [62] | i Lie | i<br>Rigsby et al., 2000 [29] (Cue-dosing) :<br>Safren<br>Rigsby et al., 2000 [29] (Cue-dosing plus cash reinforcement) |<br><!-- End of picture text -->

<!-- Start of picture text --> Stenzel et al., 2001 [66] ;_—<br>Tesoriero<br>Tuldra etet al ., , 2020 0 03 [ 3167 ] “he |<br>2 4 0 1 2 3<br>Fffect Size<br><!-- End of picture text -->
<!-- Start of picture text --> Relative risk (95% Cl) Relativerisk (95% Cl)<br>Wohl et al (2006)" 1.00 (0-75-13)<br>Macalino et al 2007)" } 143 (1-01-2.64)}<br>Sama et al (2008) ! 0.90 (073-112)<br>Taiwo et al (2008)* = = 1.23 (105-144)<br><!-- End of picture text --> <!-- Start of picture text --> Mary et al (2009)” 142 (076-138)<br>Nachega et af 2009)" O89 (071-112)<br>Gross et al 2009)" 072 (051-102)<br>Naidoo<br>et af (2009)* ! 0.95 (068-133)<br>Bangsberg et al (2009)" 1.44 (0-72-2-89)<br>Arreten et al (2009)" 1.60 ¢0-98-2-62)<br><!-- End of picture text --> <!-- Start of picture text --> Overall 1-04 (0-93-1-20)<br>a5 19 20 30<br>——_ =—_*<br>Seit-admmnestered DOT better<br>treatment better<br><!-- End of picture text -->
<!-- Start of picture text --> Study RCT Intervention Control RR 95% Cl<br>n/N n/N TT<br>Altice et al. . 49/88 26/53 1.135 0.81 1.58 — —<br>Arnsten et al. * 26/32 26/30 0.938 0.75 1.47 ——<br>Babudieri et al. 23/37 16/47 1.826 1.14 2.92 SS<br>Bangsberg etal. * 24/51 5/30 2.824 1.21 6.62 Ss<br>Gross et al. * 75/82 138/161 1.067 0.97 1.17 iy<br><!-- End of picture text -->

|Study<br>|RCT<br>|Intervention<br>n/N<br>|Control<br>n/N<br>|RR<br>|95% <br>T<br>|Cl<br>T<br>|||
|---|---|---|---|---|---|---|---|---|
|Altice et al.|.|49/88|26/53|1.135|0.81|1.58|—<br>—||
|Arnsten et al.|*|26/32|26/30|0.938|0.75|1.47|——||
|Babudieri et al.||23/37|16/47|1.826|1.14|2.92|SS||
|Bangsberg etal.<br>|*<br>|24/51<br>|5/30<br>|2.824<br>|1.21<br>|6.62<br>|S<br>|s|
|Gross et al.|*|75/82|138/161|1.067|0.97|1.17|iy||
|Horta et al.<br>|*|174/211<br>|91/211<br>|1.912<br>|1.62<br>|2.26<br>|+<br>||
|Idoko et al.<br>||42/46<br>|41/52<br>|1.158<br>|0.98<br>|1.37<br>|—_<br>||
|Lucas et al.||46/82|24/75|1.753|1.20|2.57|—_———||
|Macalino et al.|*|9/44|11/43|0.800|0.37|1.73|a||
|Munozetal.||46/60|35/60|1.314|1.02|1.70|_=||
|<br>Nachegaetal.|*|88/136|85/136|1.035|0.86|1.24|<br>——||
|Taiwo et al.|:|154/250|125/250|1.232|1.05|1.44|+||
|Tinoco et al.||26/47|26/51|1.085|0.75|1.57|—=—||
|Wohl et al.|.|44/82|45/84|1.002|0.75|1.33|——||
|RESummary<br>||||1.24<br>|1.08<br>|1.41<br>|>||
|Heterogeneity|||p<0.001|P=80.3%|67.8%|87.9%|**r**r<br>s<br>r|s||
||||||||0.5<br>1.0<br>2.0|<br>4.0|

<!-- Start of picture text --> Horta et al. * 174/211 91/211 1.912 1.62 2.26 +<br>Idoko et al. 42/46 41/52 1.158 0.98 1.37 —_<br>Lucas et al. 46/82 24/75 1.753 1.20 2.57 —_———<br>Macalino et al. * 9/44 11/43 0.800 0.37 1.73 a<br>Munoz et al. 46/60 35/60 1.314 1.02 1.70 _ =<br>Nachegaetal. * 88/136 85/136 1.035 0.86 1.24 ——<br>Taiwo et al. : 154/250 125/250 1.232 1.05 1.44 +<br><!-- End of picture text --> <!-- Start of picture text --> Tinoco et al. 26/47 26/51 1.085 0.75 1.57 —=—<br>Wohl et al. . 44/82 45/84 1.002 0.75 1.33 ——<br>RE Summary 1.24 1.08 1.41 ><br>Heterogeneity p<0.001 P=80.3% 67.8% 87.9%<br>r r srs |<br>0.5 1.0 2.0 4.0<br><!-- End of picture text -->
# **Figure 4: FEATS study design as per original protocol**

|**Group A**<br>:|**Group B**<br>:|
|---|---|
|216 ART households receiving<br>_treatment and support provided in_<br>_the existing programme_|216 ART households: A +<br>_bi-weekly visits by trained ARV_<br>_peer adherence supporter (PAS)_|
|**Group C**<br>:|**Group D**<br>:|
|216 ART households: A + B +<br>_nutritional supplement (canned_<br>_food) delivered by PAS_|208 comparison households<br>randomly sampled from the<br>relevant communities|

20
# **Figure 5: Assignment and uptake of FEATS experiments, by intervention arm**

<!-- Start of picture text --> adherence and nutritional<br>adherence support only control<br>support<br>A. Assignment phase: master reserve cross-over master reserve cross-over<br>1. master 216 216 216 [a = master]<br>2. reserve 74 75 149 [b = reserve]<br>3. total [1+2] 290 291 67 [c = a - b]<br>B. Recruitment phase:<br>4. contacted 146 28 154 31<br>174 185<br>5. not contacted 70 62 132 [d]<br>46 44 90 [e]<br>116 106 222 [f = d + e]<br>6. refused treatment offer 9 2 8 3 22 [g]<br>11 11<br>7. offered treatment [4-6] 137 26 146 28<br>163 174<br>8. cross-over during enrolment 2 2 4<br>7 6 1<br>9. enrolment [7-8] 135 24 7 140 27 4 311 [h = c + f + g]<br>166 171 311 [i]<br>C. Treatment phase:<br>10 . pre-treatment dropout 9 1 0 4 0 4<br>10 8 18 [j]<br>11. uptake [9-10] 126 23 7 136 23 4<br>156 163 329 [k = i + j]<br>12. cross-over between treatment arms 22 2 2 26<br>14 1 0 13<br>10 10 20 [l]<br>24 36<br>13. treatment 154 185 309 [m = k - l]<br>64 [n]<br><!-- End of picture text --> 21
**Table 1: Selected baseline socio-demographic and pre-ART baseline CD4 count**

||**Full cohort at**<br>**baseline**<br>**(n=654)**|**Balanced**<br>**cohort**<br>**(n=421)**|**Respondents**<br>**lost to follow-**<br>**up**<br>**(n=233)**||
|---|---|---|---|---|
|Median age (years) [IQR]|37 [31-43]|37 [32-44]|36 [31-41]|**|
|Female (%)|76.8|69.2|62.4||
|Marital status:|||||
|Single|66.9|69.2|62.4||
|Not cohabiting with partner|9.6|8.9|11.0||
|Cohabiting with partner|23.5|21.9|26.6||
|_Total_|_100.0_|_100.0_|_100.0_||
|Dwelling:|||||
|Formal|74.3|74.1|74.7||
|Informal|19.7|20.1|18.9||
|Traditional|6.0|3.7|6.4||
|_Total_|_100.0_|_100.0_|_100.0_||
|Education:|||||
|None|2.5|3.4|0.9||
|Primary|27.0|26.0|29.2||
|Some secondary|47.8|47.6|48.1||
|Grade 12|19.9|20.0|19.9||
|Tertiary|2.7|3.1|1.9||
|_Total_|_100.0_|_100.0_|_100.0_||
|Median household size [IQR]|3 [2-4]|3 [2-4]|3 [3-4]||
|Mean dependency ratio (%)|33.3|33.3|33.3||
|Medianbaseline CD4[IQR]|127 [74.5-183.5]|129.5 [77-180]|185 [66-185]||

_Note_ : Results are for patients recruited into the FEATS study cohort at baseline in 2007/08. Baseline CD4 values represent the CD4 count observed closest to but prior to ARV treatment initiation. Some percentages may not add up to 100% across categories due to rounding. One, two and three asterisks denote differences that are statistically significant at the 10%, 5% and 1% levels, respectively.

_Source_ : Authors’ own calculations.

22
**Figure 6: Kaplan-Meier survival function, by treatment arm**

_Source_ : Authors’ own calculations.

23
# **Table 2: Socio-demographic and other selected participant characteristics at baseline, by original intent-to-treat status**

||Control|[1]|Peer adhe|rence sup<br>[2]|<br>port only|Peer adhere<br>su|nce and<br>pport [3]|<br>nutritional<br>|Tota|l|
|---|---|---|---|---|---|---|---|---|---|---|
||mean|n|mean|n|p-value[a]|mean|n|p-value[b]|mean|n|
|Mean age (years)|37.6|215|37.1|214|0.306|37.5|212|0.470|37.4|641|
|Female (%)|76.8|212|75.8|211|0.399|77.5|209|0.439|76.7|632|
|Education:|||||||||||
|None|3.3|7|0.9|2|0.291|3.3|7|0.975|2.5|16|
|Primary|27.0|57|28.1|59||26.0|54||27.0|170|
|Some secondary|46.4|98|50.9|107||45.4|94||47.6|299|
|Grade 12/post-secondary|23.2|49|20.0|42||25.1|52||22.7|143|
|_Total_|_100.0_|_211_|_100.0_|_210_||_100.0_|_207_||_100.0_|_628_|
|Marital status:|||||||||||
|Single|61.1|129|73.9|156|**0.016**|65.8|137|0.603|66.9|422|
|Not cohabiting with partner|10.9|23|8.5|18||9.6|20||9.6|61|
|Cohabiting with partner|27.9|59|17.5|37||24.5|51||23.3|147|
|_Total_|_100.0_|_211_|_100.0_|_211_||_100.0_|_208_||_100.0_|_630_|
|Median pre-ART initiation CD4 [IQR]|127.0|197|132.5|198|0.724|126,0|187|0.823|||
||[69-186]||[79-183]|||[73-178]|||||
|Mean monthlyincome [ZAR]|445|211|475|210|0.350|552|205|**0.069**|490|626|

_Source_ : Authors’ own calculations.

24
# **Table 3: Self-reported adherence at baseline, by original intent-to-treat status**

||Contro|l [1]|Peer adhe|rence sup<br>[2]|<br>port only|Peer adhere<br>su|nce and<br>pport [3]|<br>nutritional|Tota|l|
|---|---|---|---|---|---|---|---|---|---|---|
||mean|n|mean|n|p-value[a]|mean|n|p-value[b]|mean|n|
|**_Self-reported adherence:_**|||||||||||
|MCA adherence_baseline|-0.016|215|-0.020|214|0.485|0.065|213|0.182|0.009|642|
|CASE_continuous|15.4|215|15.4|213|0.477|15.5|212|0.163|15.4|640|
|CASE_cutoff (%)|95.3|215|94.3|214|0.327|97.1|213|0.159|95.6|642|
|**_Clinic/hospital visits:_**|||||||||||
|Missed a drug collection visit (%)|3.7|215|2.3|214|0.202|2.3|213|0.204|2.8|642|
|Missed a routine medical check-up (%)|1.3|215|1.4|213|0.495|1.8|212|0.345|1.5|640|
|Missed either drug collection/routine check-up visit (%)|5.1|215|3.2|213|0.173|3.7|212|0.251|4.0|640|
|**_Timeliness of clinic/hospital visits:_**|||||||||||
|Mean days delayed clinic visit|5.9|64|11.4|132|**0.023**|19.1|70|0.158|12.1|266|
|Median days delayed clinic visit [IQR]|0<br>[0-3]||1<br>[0-20]||**0.010**|0<br>[0-6]||0.303|0<br>[0-7]||
|Delayed clinic visit (%)|23.4||40.1||**0.010**|30.0||0.197|33.4||
|Mean days delayed hospital visit|10.8|37|13.0|74|0.316|69.7|19|**0.036**|20.7|130|
|Median days delayed hospital visit [IQR]|0||0||0.335|24||**0.010**|0||
||[0-13]||[0-21]|||[0-58]|||[0-24]||
|Delayedhospital visit (%)|32.4||37.8||0.290|68.4||**0.004**|40.7||

_Source_ : Authors’ own calculations.

25
# **Table 4: Socio-demographic and other selected participant characteristics at baseline, by actual treatment status**

||||Peer adher|ence sup<br>|port only|Peer adhere<br>|nce and<br>|nutritional|||
|---|---|---|---|---|---|---|---|---|---|---|
||Control|[1]||[2]||su|pport [3]||Total||
||mean|n|mean|n|p-value[a]|mean|n|p-value[b]|mean|n|
|Age (years)|37.4|63|37.8|153|0.385|37.8|183|0.392|37.7|399|
|Female (%)|73.0|63|77.3|150|0.251|76.5|179|0.288|76.2|392|
|Education:|||||||||||
|None|4.8|3|0.0|-|**0.010**|4.3|8|0.425|2.7|11|
|Primary|20.9|13|33.7|51||24.5|45||27.5|109|
|Some secondary|59.6|37|47.6|72||48.6|89||50.0|198|
|Grade 12/post-secondary|14.5|9|18.5|28||22.4|41||19.7|78|
|_Total_|_100.0_|_62_|_100.0_|_151_||_100.0_|_167_||_100.0_|_396_|
|Marital status:|||||||||||
|Single|61.9|39|72.3|110|0.240|71.2|129|0.259|70.2|278|
|Not cohabiting with partner|9.5|6|9.2|14||9.9|18||9.6|38|
|Cohabiting with partner|28.5|18|18.4|28||18.7|34||20.2|80|
|_Total_|_100.0_|_63_|_100.0_|_152_||_100.0_|_181_||_100.0_|_396_|
|Median pre-ART initiation CD4 [IQR]|117.0|59|120.5|144|0.362|136.0|168|**0.059**|127.0|371|
||[63-172]||[72-179]|||[80-186]|||[72-183]||
|Mean monthlyincome [ZAR]|439|63|416|150|0.401|447|179|0.460|434|392|

_Source_ : Authors’ own calculations.

26
# **Table 5: Self-reported adherence at baseline, by actual treatment status**

||||Peer adher|ence su|pport only|Peer adher|ence and|nutritional|||
|---|---|---|---|---|---|---|---|---|---|---|
||Contro|l [1]||[2]||s|upport [3]||Tota|l|
||mean|n|mean|n|p-value[a]|mean|n|p-value[b]|mean|n|
|**_Self-reported adherence:_**|||||||||||
|MCA adherence_baseline|0.037|63|-0.113|153|0.178|-0.036|183|0.326|-0.054|399|
|CASE_continuous|15.4|63|15.1|153|0.162|15.4|183|0.410|15.3|399|
|CASE_cutoff (%)|95.2|63|92.8|153|0.256|95.0|183|0.488|94.2|399|
|**_Clinic/hospital visits:_**|||||||||||
|Missed a drug collection visit (%)|6.3|63|1.9|153|**0.049**|3.2|183|0.144|3.2|399|
|Missed a routine medical check-up (%)|1.5|63|1.3|152|0.439|1.6|182|0.486|1.5|397|
|Missed either drug collection/routine check-up visit (%)|7.9|63|2.6|152|**0.038**|4.9|182|0.190|4.5|397|
|**_Timeliness of clinic/hospital visits:_**|||||||||||
|Mean days delayed clinic visit|4.1|16|11.6|122|**0,075**|13.6|128|0,314|12.1|266|
|Median days delayed clinic visit [IQR]|0||0||**0,025**|0||**0,049**|0||
||[0-16]||[0-28]|||[0-5]|||[0-7]||
|Delayed clinic visit (%)|18.7||40.1||**0,048**|28.9||0,198|||
|Mean days delayed hospital visit|2.8|15|14.1|64|**0,053**|33.8|51|0,166|20.7|130|
|Median days delayed hospital visit [IQR]|0||0||**0,047**|5||**0,004**|0||
||[0-0]||[0-22]|||[0-28]|||[0-24]||
|Delayedhospital visit (%)|13.3||39.0||**0,029**|50.9||**0,004**|40.7||

_Source_ : Authors’ own calculations 27
# **Table 6: Self-reported adherence, by intent-to-treat status**

||Control [1]|Peer adherence<br>support only [2]|Peer adherence a<br>nutritional suppor<br>[3]|p-value[a<br>nd<br>t|]<br>Any peer adhere<br>support [4]|p-value[b]<br>nce|
|---|---|---|---|---|---|---|
|**_Self-reported adherence:_**|||||||
|MCA adherence index|-0.008 (0.06)|0.027 (0.06)|0.006 (0.07)|0.929|0.017 (0.05)|0.749|
|CASE index|15.3 (0.1)|15.4 (0.1)|15.3 (0.1)|0.956|15.3 (0.1)|0.855|
|CASE_cutoff (%)|94.9 (1.4)|95.4 (1.4)|93.8 (1.7)|0.781|94.7 (1.1)|0.912|
|**_Clinic/hospital visits:_**|||||||
|Missed either drug collection/routine check-up visit (%)|6.9 (1.6)|8.5 (2.0)|3.4 (1.3)|0.126|6.2 (1.2)|0.737|
|**_Timeliness of clinic/hospital visits:_**|||||||
|Mean days delayed clinic visit|11.1 (1.0)|9.6 (1.0)|8.8 (1.0)|0.319|9.2 (0.7)|0.159|
|Delayed clinic visit (%)|30.1 (1.7)|24.1 (1.5)|20.8 (1.3)|**<0.001**|22.4 (1.0)|**<0.001**|
|Mean days delayed hospital visit|15.3 (1.9)|12.2 (1.7)|15.3 (2.5)|0.476|13.7 (1.5)|0.511|
|Delayedhospital visit (%)|36.2(2.6)|34.3 (2.6)|34.2(2.7)|0.832|34.3 (1.9)|0.545|

_Source_ : Authors’ own calculations.

28
# **Table 7: Self-reported adherence, by treatment status**

||Control [1]|Peer adherence<br>support only [2]|Peer adherence a<br>nutritional suppor<br>[3]|p-value[a<br>nd<br>t|]<br>Any peer adheren<br>support [4]|p-value[b]<br>ce|
|---|---|---|---|---|---|---|
|**_Self-reported adherence:_**|||||||
|MCA adherence index|-0.100 (0.13)|-0.095 (0.09)|0.089 (0.06)|0.210|0.004 (0.05)|0.435|
|CASE index|15.1 (0.2)|15.3 (0.1)|15.5 (0.1)|0.325|15.4 (0.1)|0.291|
|CASE_cutoff (%)|93.5 (2.7)|94.4 (1.9)|95.2 (1.6)|0.874|94.8 (1.2)|0.662|
|**_Clinic/hospital visits:_**|||||||
|Missed either drug collection/routine check-up visit (%)|8.8 (3.2)|7.3 (2.2)|1.5 (0.9)|0.021|4.2 (1.1)|0.112|
|**_Timeliness of clinic/hospital visits:_**|||||||
|Mean days delayed clinic visit|13.7 (1.4)|9.6 (1.0)|8.6 (0.8)|**0.016**|9.0 (0.6)|**0.005**|
|Delayed clinic visit (%)|37.8 (48.5)|22.8 (42.0)|22.1 (41.5)|**<0.001**|22.4 (41.7)|**<0.001**|
|Mean days delayed hospital visit|17.6 (2.5)|13.5 (2.0)|13.3 (1.8)|0.375|13.4 (1.3)|0.162|
|Delayedhospital visit (%)|39.3 (48.9)|34.2(47.5)|33.5 (47.5)|0.342|33.8 (47.3)|0.146|

_Source_ : Authors’ own calculations.

29
# **Figure 7a: Mean and median delay in scheduled clinic visits (days), by treatment arm**

<!-- Start of picture text --> 18<br>16<br>14 13,8<br>12<br>10<br>9,7<br>9,0 9,1<br>8<br>6<br>4<br>2<br>0<br>Control PAS only Any PAS Food<br><!-- End of picture text -->

**Figure 7b: Late for a scheduled clinic visit (%), by treatment arm**

<!-- Start of picture text --> 45<br>40<br>37,8<br>35<br>30<br>25<br>20 22,8 22,4 22,1<br>15<br>10<br>5<br>0<br>Control PAS only Any PAS Food<br><!-- End of picture text --> _Note:_ Figures represent means with 95% confidence intervals.

_Source_ : Authors’ own calculations.

30
**Figure 8a: Mean and median delay in scheduled hospital visits (days), by treatment arm**

<!-- Start of picture text --> 25<br>20<br>17,6<br>15<br>13,6 13,4 13,3<br>10<br>5<br>0<br>Control PAS only Any PAS Food<br><!-- End of picture text -->

**Figure 8b: Late for a scheduled hospital visit (%), by treatment arm**

<!-- Start of picture text --> 50<br>45<br>40 39,4<br>35 34,2 33,9 33,6<br>30<br>25<br>20<br>15<br>10<br>5<br>0<br>Control PAS only Any PAS Food<br><!-- End of picture text --> _Note:_ Figures represent means with 95% confidence intervals.

_Source_ : Authors’ own calculations.

31
# **Table 8: Effects of Peer Adherence Support (PAS) and Food on Self-Reported Adherence**

||MCA adherence<br>index|CASE adherence<br>index|CASE cut-off|Missed a drug<br>collection visit|Missed a routine<br>check-up|Missed a clinic or<br>hospital visit|
|---|---|---|---|---|---|---|
|**A. Intent-to-treat analysis**|||||||
|Treatment|-0.304 *|-0.783 ***|-0.072 **|0.017|0.028|0.014|
|Treatment * ITT PAS only|0.086|0.275|0.041|**0.052 ***|0.006|**0.065 ***|
|Treatment * ITT PASnFood|-0.020|-0.071|-0.006|0.013|-0.038|0.001|
|n (N)|618 (1,270)|617 (1,268)|618 (1,270)|618 (1,267)|618 (1,263)|618 (1,263)|
|F-test (p-value)|1.05 (0.384)|2.11 (0.062)|1.6 (0.157)|1.65 (0.143)|1.95 (0.084)|1,61 (0.154)|
|Treatment|-0.307 *|-0.792 ***|-0.073 **|0.016|0.027|0.012|
|Treatment * ITT AnyPAS|0.034|0.106|0.018|0.033|-0.015|0.034|
|n (N)|618 (1,270)|617 (1,268)|618 (1,270)|618 (1,267)|618 (1,263)|618 (1,263)|
|F-test (p-value)|1.19 (0.315)|2.19 (0.068)|1.32 (0.261)|1.68 (0.153)|1.73 (0.142)|1.20 (0.310)|
|**B. Instrumental variable (IV) analysis**|||||||
|Treatment|-0.150|-0.706|-0.080|-0.028|0.065|-0.019|
|Treatment * PAS only|-0.085|0.223|0.084|0.094|0.011|0.120|
|Treatment * PASnFood|-0.097|0.055|0.026|0.027|**-0.099 ***|-0.000|
|n (N)|388 (794)|388 (794)|388 (794)|388 (792)|388 (790)|388 (790)|
|F-test (p-value)|4.05 (0.670)|60,634 (<0.001)|16,730 (<0.001)|35.35 (<0.001)|31.45 (<0.001)|47.04 (<0.001)|
|Treatment|-0.150|-0.699|-0.077|-0.026|0.067|-0.017|
|Treatment * AnyPAS|-0.093|0.113|0.046|0.051|-0.059|0.043|
|n (N)|388 (794)|388 (794)|388 (794)|388 (792)|388 (790)|388 (790)|
|F-test(p-value)|4.06(0.541)|60,703(<0.001)|16,780(<0.001)|33.55(<0.001)|26.00(<0.001)|42.80(<0.001)|

_Note_ : Results are for Fixed Effect (FE) Instrumental Variables (IV) linear panel regression models. Results are adjusted for age, sex, education and treatment duration. _Source_ : Authors’ own calculations.

32
# **Table 9: Effects of Peer Adherence Support (PAS) and Food on Timeliness of Visits**

||Clinic - delay (days)|Clinic - delayed<br>(yes/no)|Hospital - delay<br>(days)|Hospital - delayed<br>(yes/no)|
|---|---|---|---|---|
|**A. Intent-to-treat analysis**|||||
|Treatment|6.197|0.089|10.321|0.192 *|
|Treatment * ITT PAS only|-0.589|-0.105|7.372|-0.110|
|Treatment * ITT PASnFood|-5.794|**-0.177 ***|**-22.587 *****|**-0.456 ****|
|n (N)|192 (2,108)|192 (2,108)|114 (844)|114 (844)|
|F-test (p-value)|2.07 (0.082)|2.37 (0.050)|3.60 (0.006)|1.78 (0.131)|
|Treatment|6.163|0.089|10.091 *|0.189 *|
|Treatment * ITT AnyPAS|-2.979|**-0.138 ***|-3.235|-0.232|
|n (N)|192 (2,108)|192 (2,108)|114 (844)|114 (844)|
|F-test (p-value)|2.34 (0.071)|2.95 (0.031)|1.79 (0.147)|1.26 (0.288)|
|**B. Instrumental variable (IV) analysis**|||||
|Treatment|9.798|0.335|24.396 **|0.525 **|
|Treatment * PAS only|-0.650|-0.301|-1.047|-0.408|
|Treatment * PASnFood|-10.623|**-0.439 ***|**-39.827 ****|**-0.821 ****|
|n (N)|192 (2,108)|192 (2,108)|108 (801)|108 (801)|
|F-test (p-value)|374.48 (<0.001)|793.73 (<0.001)|219.99 (<0.001)|420.28 (<0.001)|
|Treatment|12.134|0.367|17.127|0.447 **|
|Treatment * AnyPAS|-8.924|**-0.415 ***|-14.296|**-0.549 ****|
|n (N)|192 (2,108)|192 (2,108)|108 (801)|108 (801)|
|F-test(p-value)|374.24(<0.001)|795.81(<0.001)|214.44(<0.001)|423.11(<0.001)|

_Note_ : Results are for Fixed Effect (FE) Instrumental Variables (IV) linear panel regression models.

Results are adjusted for age, sex, education and treatment duration.

_Source_ : Authors’ own calculations.

33
**Table 10: Effects of Peer Adherence Support (PAS) and Food on CD4 counts**

|**Variables**|**[1]**|**[2]**|**[3]**|**[4]**|
|---|---|---|---|---|
|PAS only|60.329<br>(1.96)*|55.539<br>(1.62)|||
|PAS and Food|25.565<br>(0.92)|27.507<br>(0.89)|||
|Female|14.565|14.979|18.730|18.984|
||(0.96)|(0.99)|(1.26)|(1.41)|
|ARV treatment duration (months)|65.189|65.804|66.720|65.893|
||(5.57)**|(5.58)**|(5.68)**|(4.44)**|
|Female * ARV treatment duration (months)|12.056|11.963|11.730|9.635|
||(4.14)**|(4.11)**|(4.04)**|(2.65)**|
|Age|‐9.716|‐9.670|‐9.423|‐9.868|
||(3.71)**|(3.68)**|(3.62)**|(4.18)**|
|Age * ARV treatment duration (months)|‐0.633|‐0.653|‐0.651|‐0.477|
||(1.25)|(1.29)|(1.28)|(0.75)|
|ARV treatment duration (months)<sup>2</sup>|‐2.502|‐2.592|‐2.980|‐3.243|
||(3.81)**|(3.23)**|(3.94)**|(3.62)**|
|Mills ratio|‐16.024|‐17.793|7.319|61.056|
||(0.14)|(0.15)|(0.07)|(0.98)|
|PAS only * FEATS duration (months)||3.213|7.510|12.624|
|||(0.67)|(1.84)|(2.37)*|
|PAS and Food * FEATS duration (months)||‐1.081|0.920|‐3.097|
|||(0.26)|(0.26)|(0.68)|
|Constant|315.331|315.222|323.130|319.195|
||(5.15)**|(5.13)**|(5.33)**|(5.95)**|
|_N (n)_|2,733|2,733|2,733|2,733|
||(549)|(549)|(549)|(549)|
|Chi2|1,504.01|1,506.60|1,511.13|1,044.06|

_Note_ : Results are for Random Effects (RE) Instrumental Variables (IV) linear panel regression models with robust standard errors. Continuous variables are entered into the regression as square roots. Adjusted for selection bias using the Mills ratio.

_Source_ : Authors’ own calculations.

34
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