The global scale up of antiretroviral therapy (ART) has shown remarkable progress during the last decade, with now more than 15 million individuals receiving ART [1,2]. The greatest increase has occurred in sub-Saharan Africa (SSA), where more than 11 million have received ART . As of July 2014, ART has been associated with a 35% decline in AIDS-related mortality to approximately 1.7 million, compared with 2005 (and a 32% decline in SSA), although the region still accounts for 70% of all persons dying from AIDS [1,2]. This has been made possible through adoption of a public health approach to treatment scale up, whereby the implementation of simplified and standardized approaches (such as simplified treatment regimens as part of fixed-dose combinations, and decentralization of services) ensures the widest possible access to high-quality services at the population level .
There has been a steady increase in the median CD4+ cell count at ART initiation in SSA [4,5], in accordance with successive WHO guidelines, less than 200 cells/μl in 2006 , less than 350 cells/μl in 2010 , less than 500 cells/μl in 2013 , and now ‘treat all’ regardless of CD4+ cell count in 2015 . However, late presentation and diagnosis remains common in many settings, and so ART is often initiated when disease is already advanced and CD4+ cell counts are well below the recommended threshold. Late initiation of ART is associated with a high risk of early mortality, mainly due to HIV-related opportunistic infections especially in the first year before there has been sufficient time for adequate immune reconstitution, but also due to ART-related immune reconstitution inflammatory syndrome [10–12].
Although data on the distribution of the CD4+ cell count at ART initiation in adults is well documented in the literature [3,5,10], the subsequent CD4 response has been less well described, and in particular the proportion that remain profoundly immunosuppressed and at risk for opportunistic infections. Factors associated with suboptimal immune recovery (SO-IR) include older age [11–14], gender [15–18], advanced HIV disease at ART initiation , coinfections such as tuberculosis (TB) , hepatitis C  and persistent immune activation [13–15], and it is presumed to be mediated by severe HIV-associated immune dysfunction [21–23]. Even those who immune reconstitute to above 200 cells/μl (the level above which they are at a substantially lower risk of opportunistic infections) but below 500 cells/μl remain at risk for non-AIDS-defining events such as liver, cardiovascular and renal diseases , and other comorbidities due to persistent immune activation [24–27]. Moreover, a recent landmark the Strategic Timing of Anti-Retroviral Therapy trial (START) showed that starting ART when the CD4+ cell count is above 500 cells/μl (compared with <350 cells/μl) more than halved the risk of AIDS events, deaths as well as serious non-AIDS events .
A range of definitions have been used to determine SO-IR at different time points after ART initiation. These include a magnitude of CD4+ cell count increase of less than 50 cells/μl after 6 months , or less than 100 cells/μl after 12 months [12,30], and an absolute CD4+ cell count remaining below 200 cells/μl after 24 months [31,32], or below 500 cells/μl after 60 months  as well as variations in longitudinal analyses . Understanding the proportion of patients who fail to attain CD4+ cell count levels above 200, 350 and 500 cells/μl has important programmatic implications. Those patients with SO-IR, and particularly CD4+ cell counts less than 200 cells/μl will require closer monitoring for the development of AIDS-defining and non-AIDS-defining clinical events, as well as more prolonged prophylaxis (e.g. with cotrimoxazole and isoniazid). The objective of our analysis was three-fold: first, to quantify the proportion with a CD4+ cell count below 200, 350 and 500 cells/μl (reflecting the incremental WHO thresholds for ART initiation) during the first 5 years post-ART initiation; second, to describe clinical consequences of SO-IR and, third, to identify factors associated with suboptimal immune response.
Study setting and participants
The International epidemiologic Databases to Evaluate AIDS (IeDEA) network is an international research consortium, established in 2005 by the National Institute of Allergy and Infectious Diseases, that pools data from geographically dispersed cohorts to address regionally important epidemiological and HIV programmatic questions. Cohorts from all seven sites in the IeDEA East African region were included in this analysis, and dates of last available data or database closure are given in parentheses. These included three sites in Uganda, Mbarara Immune Suppression Syndrome Clinic (31 December 2009), Masaka Regional Hospital HIV Clinic (13 June 2011) and Infectious Diseases Institute, Makerere University (24 May 2011), two programs in western Kenya: Academic Model Providing Access to Healthcare (AMPATH) sites (27 July 2011) and Family AIDS Care and Education Services (FACES) sites (30 May 2011), and in Tanzania, Ocean Road Cancer Institute – (ORCI) (14 July 2010), and Tumbi Special Hospital (18 September 2008). Analysis was conducted on de-identified data, and patients were not individually consented to participate. All research in IeDEA is overseen by institutional review boards or ethics committees in the countries where data are collected, and by ethics committees with oversight over the analytical teams [4,5].
Within this region, we included all adult patients (≥18 years at ART initiation) enrolled at one of the East Africa sites, who initiated an ART regimen that contained at least three drugs (according to the national HIV treatment guidelines), and had received at least 6 months of ART and remained in care. At the time, patients were initiated on stavudine, lamivudine/zidovudine and nevirapine/efavirenz, with efavirenz given mainly for patients with TB and lamivudine for patients with hemoglobin levels below 8 g/dl; and one-drug regimen switches were recommended in cases of drug toxicities. Sociodemographic and clinical variables such as sex, age, ART regimen, and the dates of clinical events (ART initiation, follow-up visits and HIV-related illnesses including but not limited to oral and esophageal candidiasis, pulmonary TB, chronic diarrhea, herpes zoster eruptions, Kaposi's sarcoma, cryptococcal meningitis, Pneumocystis carinii pneumonia and papular pruritic eruptions), and CD4 measurements collected during the course of routine care (generally every 6 months) were available for analysis. Adherence support was provided routinely and patient adherence to ART was self-reported at 95% at least within the ART programs. Routine viral load monitoring was not available in the sites at the time of analysis.
Definition of suboptimal immune recovery
A variety of different definitions have been used in clinical trials [33,34], observational cohorts [31,32], pathogenesis studies [19,35] to define suboptimal recovery. In this analysis, we defined SO-IR as failure to attain three different CD4+ cell count thresholds during the first 5 years of first-line antiretroviral therapy: 200 cells/μl (SO-IR200), below which individuals remain at particular risk of life-threatening opportunistic infections [22,23]; 350 cells/μl (SO-IR350) – the recommended threshold for ART initiation in the WHO 2010 guidelines  and 500 cells/μl (SO-IR500) – the recommended threshold for ART initiation in WHO 2013 guidelines . CD4+ cell counts above 500 cells/μl are considered normal relative to the average CD4+ cell counts of ≥500 cells/μl among healthy Africans . Baseline CD4+ cell count at ART initiation was defined as the most recent CD4+ cell count in the 2 months prior to ART initiation and a follow up CD4+ cell count was defined as the most recent CD4+ cell count within 2 months before and after the respective analysis time. Baseline variables at ART initiation included in the model were sex, age, BMI, WHO clinical stage, CD4+ cell count and ART regimen. Proportions of ART-treated patients in the three categories of SO-IR were calculated during the first 5 years of the ART programs.
Opportunistic infections and suboptimal immune recovery
Kaplan–Meier survival analysis techniques were used to assess the cumulative probability of suboptimal immune recovery, with competing risks of death or loss to follow-up. Using survival analysis, the incidence rates of HIV-related opportunistic infections and related illnesses during the first 5 years following ART initiation were obtained, and reported for the period (below the CD4+ cell count thresholds of 200, 200–350, 351–499 cells/μl and >500 cells/μl. Individuals were censored at switch to second-line ART, death, loss to follow-up (defined as those with no clinic visit 6 months or more prior to database closure), database closure and at attainment of CD4+ cell counts 200–350 and 351–499 cells/μl for the respective analyses.
The respective rates of HIV-related illnesses among these CD4 strata were expressed as incidence rates per 100 PYAR, with 95% confidence intervals (CIs). Reductions in incidence rate (after attainment of the different CD4 thresholds) were expressed as percentage reductions. Predictors of SO-IR, using the three thresholds, were determined in a Cox proportion hazard model. Missing data on baseline CD4+ cell count were imputed using chained equations. All analysis was carried out using STATA 12 (Copyright 1985–2011. StataCorp LP, College Station, Texas, USA).
Patients eligible for inclusion in analysis of rate of suboptimal immune recovery
Overall, 83 926 initiated ART at the seven IeDEA sites in East Africa, of whom 3083 (3%) were excluded because records showed that they had initiated less than three antiretroviral drugs. Each year, between 9 and 32% of patients were lost to follow-up, with the highest numbers lost to follow-up in the first 3 years after ART initiation. Between 21 and 64% of the patients in care at each of the respective time points were not eligible for analysis of SO-IR because they did not have a CD4+ cell count measurement at or within 2 months before and after the respective time point (Table 1).
Patient characteristics at antiretroviral therapy initiation
Of the 80 843 patients initiating a triple antiretroviral drug regimen, 65% were women, and at ART initiation, the median age was 36 years; interquartile range (IQR) (30–43), BMI median was 20.1 kg/m2 (IQR, 17.9–22.5), median CD4+ cell count was 126 cells/μl (IQR, 52–202), median hemoglobin was 11.3 g/dl (IQR, 9.7–12.9). The majority (97%) initiated an non-nucleoside reverse transcriptase inhibitor-based regimen. Baseline demographic and clinical characteristics at ART initiation were similar across the three countries, but Tanzania had a low hemoglobin level: 9.6 g/dl (7.9–11.4) versus 11.2 g/dl (9.6–12.8) and 11.7 g/dl (10.2–13.1) for Kenya and Uganda respectively, although the differences were not statistically significant (Table 2).
Cumulative proportion with suboptimal immune recovery
Overall, the proportions of ART-treated adults with SO-IR declined as absolute CD4+ cell counts increased over the duration of ART. The proportion with CD4+ cell counts less than 200 cells/μl reduced from 36% after 6 months of ART to 20% after 24 months and 11% after 60 months, and the proportion with a CD4+ cell count less than 350 cells/μl reduced from 71% after 6 months of ART to 58% after 24 months and 38% after 60 months, and those with CD4+ cell counts less than 500 cells/μl reduced from 89% after 6 months of therapy to 80% after 24 months and 63% after 60 months of therapy (Table 3).
HIV-related illnesses before and during immune recovery
Using survival analysis techniques, we examined the cumulative probability of SO-IR [remaining with CD4+ cell count thresholds below 200 cells/μl SO-IR200], between 200 and 350 cells/μl SO-IR 350 and between 351 and 500 cells/μl SO-IR 500 at each year during the first 5 years following ART initiation, taking into account the competing risks of death and loss to follow-up. Overall, there was 132 356 PYAR with CD4 cells counts less than 200 cells/μl, 127 758 PYAR >200 ≤ 350 cells/μl, and 105 823 PYAR > 350 ≤ 500 cells/μl.
The most common opportunistic infections prior to achieving CD4+ cell count threshold above 200 cells/μl were pulmonary TB [incident rate, per 100 person-years (95% CI), 15.98 (15.47–16.51)] oral candidiasis [12.5 (12.03–12.94)], herpes zoster [6.30 (5.99–6.64)] and chronic diarrhea [5.48 (5.18–5.78)]. After attainment of a CD4+ cell count threshold above 200 cells/μl (between 200 and 350 cells/μl), there was a substantial reduction in event rates of opportunistic infection events by 91% to 1.45 (1.29–1.63) for TB, by 94% to 0.75 (0.64–0.89) for oral candidiasis, by 84% to 0.99 (0.86–1.14) for herpes zoster, and by 78% to 1.22 (1.07–1.39) for chronic diarrhea (Table 4).
When the CD4+ cell count > 350 < 500 cells/μl strata was considered, pulmonary TB, chronic diarrhea and pruritic purpura eruptions were the commonest HIV-related events at incident rates of 1.05 (0.87–1.27), 1.08 (0.89–1.31) and 1.11 (0.92–1.34), respectively. After attainment of CD4 counts CD4 >500 cells/μl, AIDS related events such as pneumocystis carinii pneumonia, cryptococcal meningitis, extrapulmonary TB and toxoplasmosis were not observed (Table 4).
Factors associated with suboptimal immune recovery
In a multivariate analysis model we identified factors associated with SO-IR. Factors significantly associated with SO-IR200 were older age (every 5 year increase in age), sub-hazard ratio (SHR) [95% CI, 1.01 (1.00–1.03), male gender, SHR 1.14 (1.08–1.20), baseline CD4+ cell count less than 100 cells/μl versus more than 100 cells/μl, SHR 0.89 (0.80–0.99), and hemoglobin level below 10 mg/dl versus 10 mg/dl and above, SHR 1.39 (1.29–1.48)], as shown in Table 5. The risk factors that were significant and magnitude of effect were similar across the different SO-IR CD4+ cell count thresholds of 200, 350 and 500 cells/μl. Baseline weight above 60 kg had a modest but statistically significant association with SO-IR 350 [SHR 1.04 (1.01–1.08)] and SO-IR 500 [SHR 1.05 (1.02–1.07)].
This analysis of around 80 000 HIV-infected persons from HIV care programs in Kenya, Uganda and Tanzania who initiated mainly non-nucleoside reverse transcriptase inhibitor-based ART regimens between 2005 and 2011 at a median CD4+ cell count of 126 (52–202) cells/μl, represents the most comprehensive study of the frequency and consequences of suboptimal immune reconstitution to date. At 12 months, 29% of ART-treated patients in care with follow-up CD4+ cell counts (±within 2 months), had suboptimal immune recovery (SO-IR) with CD4+ cell counts less than 200 cells/μl, 66% and 87% had SO-IR with CD4+ cell counts below 350 and 500 cells/μl, respectively. Proportions of SO-IR declined with increasing duration of ART to 11% below 200 cells/μl, 38% below 350 cells/μl and 63% below 500 cells/μl, after 5 years of ART.
SO-IR was associated with high rates of HIV-related opportunistic and other illnesses, and the commonest events were pulmonary TB, oral candidiasis and herpes zoster, followed by papular pruritic eruptions, chronic diarrhea, recurrent respiratory tract infections, esophageal candidiasis, Kaposi's sarcoma, chronic herpes simplex and pneumocystis pneumonia. In our current study, immune recovery to at least 200–350 cells/μl was associated with over 90% reduction in incidence of all opportunistic infections to an incidence rate of less than 1 per 100 person-years for all reported events except TB, chronic diarrhoea papular pruritic eruptions and respiratory tract infections. A similar pattern was observed for opportunistic infections in other CD4+ cell threshold categories. Although in a previous analysis from one of the clinic sites in Uganda, we reported comparable HIV-related events among optimal and suboptimal responders in the Infectious Diseases Institute (IDI) research cohort in Uganda, the latter study was based on only 380 persons with 123 events during a 2-year period of follow-up . Therefore, using data from seven IeDEA sites, including IDI, substantially increased the statistical power to detect a higher incidence of opportunistic infections among SO-IR compared to optimal immune responders (OP-IR).
Other studies have shown similar rates of CD4+ cell counts persisting below 200 cells/μl, 350 and 500 cells/μl, and a continued high rate of clinical events during ART [32–34,37,38]. Even in settings where there is routine monitoring of viral load, data show that although the majority of those who are virologically suppressed achieve good immune recovery, up to 40% still exhibit SO-IR [39,40]. In the United Kingdom Collaborative HIV cohort study , ART-treated patients with CD4+ cell counts 350–499 cells/μl had an opportunistic infection rate of 2.49 per 100 person-years, which was reduced to a rate of 1.54 per 100 person-years in those with a CD4+ cell count 500–649 cell/μl and 0.96 per 100 person-years among those with CD4+ cell counts above 650 cells/μl. In another multicenter study in Europe, ART-treated patient with suboptimal immune recovery (CD4 reported to gain of less than 50 cells after 1 year) had higher post-ART mortality of 3.22 per 100 person-years versus 0.71 per 100 person-years among optimal immune responders . Similarly, among 850 participants in a community program in the United States during a 5-year follow up period, both AIDS and non-AIDS disease rates declined from 13.8 to 2.1 events per 100 person-years when the most recent CD4 cell count increased from less than 200 to 200 cells/μl and from 2.0 to 1.7 events per 100 person-years when the latest CD4+ count increased from 200 to 350 cells/μl to more than 350 cells/μl .
We found that individuals with advanced HIV disease (WHO clinical stage 3 and 4, and CD4+ cell count <100 cells/μl) were less likely to have SO-IR (SO-IR200, SO-IR350 and SO-IR500). This finding was similar to our previous report from IDI (one of the contributing sites) where pre-ART CD4+ cell count ≥100 cells/μl was associated with suboptimal immune recovery (CD4+ cell count increase <50 cells/μl after 6 months and CD4+ cell count increase <200 cells/μl after 24 months of ART), when compared with individuals with pre-ART CD4+ cell counts less than 100 cells/μl . Similarly, in the IDI cohort, individuals with pre-ART CD4+ cell counts of 50–199 cells/μl were three times more likely to have suboptimal immune recovery than those with pre-ART CD4+ cell counts less than 50 cells/μl . Our results are also consistent with previous reports from South Africa where individuals with pre-ART CD4+ cell counts less than 50 cells/μl had better CD4+ cell count recovery during 48 weeks of ART compared to those with higher pre-ART CD4+ cell counts . Additional evidence from three large HIV treatment programs in South Africa, showed that patients with pre-ART CD4+ cell counts less than 50 cells/μl had a steeper gradient of CD4+ cell count increase than patients with pre-ART CD4+ cell counts between 50 and 199 cells/μl . The high CD4+ cell count recovery in these studies could be attributed to peripheral expansion and/or redistribution of CD4 T cells that is described in the initial phase of CD4 recovery during antiretroviral therapy . Our findings are contrary to reports from the Australian HIV Observational database where higher baseline CD4 T-cell counts predicted attainment of a CD4+ cell count more than 500 cells/μl .
Advanced HIV disease has been previously associated with high collagen deposition and irreversible fibrosis of the reticuloendothelial system, leading to poor immune recovery [19,22,23]. In addition, coinfections including hepatitis C virus, genetic polymorphisms and differences in regulatory T-cell function and homeostasis have been suggested to contribute to poor CD4 T-cell recovery during ART . We postulate that CD4+ cell counts may not be the best measure of immune recovery, particularly among individuals with advanced HIV disease in Africa. There is need to understand the role of other biomarkers of HIV disease progression, such as immune activation and microbial translocation markers , in enhancing the monitoring of immune recovery among individuals in SSA that initiate ART at advanced stages of disease. Measurement of HIV reservoir size could also provide additional evidence on response to ART, given the direct correlation of cell-associated HIV RNA with immune activation among ART-treated individuals .
Other factors with smaller impact on SO-IR were increased age (2–4% increased risk for each 5-year increase in age), and weight more than 60 kg. A less optimal immune response with increased age has also been reported in other studies, and among individuals older than 30 years of age [5,34], due to diminished thymus function with advancing age . Similarly, other studies have reported an association between age greater than 30 years and poorer long-term immune response to ART [10,11], including an analysis of persons who had achieved viral suppression . Patients with weight more than 60 kg at ART initiation were more likely to have SO-IR, although we were unable to use BMI due to incomplete height records. Previous reports from the North American AIDS Cohort Collaboration on Research and Design (NA-ACCORD) cohort suggest that a BMI of approximately 30 kg/m2 at ART initiation was associated with greater CD4 T-cell recovery at 12 months compared with higher or lower BMI values, suggesting that body composition may affect peripheral CD4 T-cell recovery . We therefore recommend consistent follow-up of BMI in African HIV treatment cohorts to further understand its role in host immune recovery during ART.
A key limitation and striking finding in this analysis of routinely collected data from 80 000 persons, who initiated ART across multiple sites in East Africa, is that 21–64% of patients in care, depending on site, had no record of follow-up CD4+ cell count measurements at the different follow-up time points, and were therefore excluded from the analysis of suboptimal immune recovery. Although, we found no systematic differences in demographic or clinical characteristics of those with missing data, we speculate that these persons may be more likely to have suboptimal responses and therefore the true prevalence of suboptimal immune recovery may have been underestimated. This also highlights the real-world challenges of optimal data collection in resource-limited settings, and importance of strategies to optimize retention in care to achieve full impact of ART scale up. Second, there was no routine monitoring of viral load in our study population, so we were not able to describe underlying treatment failure and development of drug resistance as independent causes of SO-IR. This retrospective data analysis did not evaluate innate host factors that may contribute to slow immune recovery. Additional strategies of ART regimen optimization or immune modulatory interventions may require formal evaluation .
What are the implications of these findings for antiretroviral programs?
First, a high proportion (around 40%) of patients initiated on ART in the absence of routine viral load monitoring did not achieve optimal immune recovery to at least a CD4+ cell count greater than 350 cells/μl and remained at risk of HIV-related opportunistic and other infections. Such patients may require closer monitoring for the development of HIV-related as well as non-HIV-defining clinical events, and consideration for long-term prophylaxis with cotrimoxazole and isoniazid. There is now an increasing emphasis on strategic use of viral load monitoring rather than CD4+ cell count monitoring to assess response to ART and identify treatment failure early on, for individuals that require ART regimen switch to second-line ART [9,32,37]. Multiple studies have shown that when sustained viral suppression is achieved, there is good immune recovery [10,49]. Among 1004 patients ART-treated patients attending the Melbourne Sexual Health Centre in Australia, routine CD4+ cell counts rarely influenced clinical decisions to stop or change treatment therefore CD4+ cell count monitoring was reduced from biannual to annual .
However, the significant proportion with SO-IR and ongoing HIV-related events in our cohort should caution ongoing discussions in countries about discontinuation of CD4+ cell count monitoring , particularly if patients have not attained CD4+ cell counts more than 500 cells/μl. Strategic monitoring of CD4+ cell count will be needed to identify those patients who remain at risk of opportunistic infections due to SO-IR based on readily available measures such as white blood cell count and lymphocyte percentage  or poor adherence [20,43]. Predictive models to identify those who will remain with a CD4+ cell count less than 200 cells/μl in the first 3 years of therapy  could be used to prioritize CD4+ cell count and viral load measurements for those with SO-IR who may require adherence support or switch to second-line ART.
The database for these analyses did not include follow-up of patients that were not receiving ART. It is evident, however, that the opportunistic infections presented here could occur at higher CD4+ cell counts, for example, TB, oral candidiasis, and herpes zoster.
Our findings, emphasize the importance of earlier ART initiation as a priority to improve clinical outcomes since patients with SO-IR remain at risk of AIDS-related events. The Strategic Timing of Antiretroviral Treatment and TEMPRANO ANRS 12 136 trials have demonstrated the profound impact of early ART at a CD4+ cell count above 500 cells/μl compared to when the CD4+ cell count declines to below 350 cells/μl [28,51], and international guidelines now recommend ART in all HIV infected persons regardless of CD4+ cell count [9,52,53]. However, even with continued progress of ART at any CD4+ cell count level in SSA [1,2], and the anticipated better immune recovery [4,33], some patients continue to initiate ART late and remain at greater risk of SO-IR. Given that all our patients initiated zidovudine/stavudine containing regimen (according to the ART guidelines and availability at the time), there is need to evaluate long-term immune recovery with the recommended newer drugs that are less toxic . It is also important to note that these analyses were limited to patients on first-line therapy and did not provide data on CD4 trajectory after treatment switch to second-line therapy following immunological failure. Similarly, this study did not analyze the effects of one-drug regimen switches due to drug toxicities, given that adherence was not altered to levels below 95%. Our results, however, remain important to ART programs in SSA since duration of first-line ART is an indicator of the success of ART programs, in addition to immunological/virological responses, survival, treatment adherence and retention in care .
Around 40% of ART-treated adults in East Africa had suboptimal immune recovery with CD4 counts <350 cells/μl after the initial 5 years of first-line antiretroviral therapy, and this was associated with ongoing incident HIV-related illnesses. This has important programmatic implications, as these patients require closer monitoring for the development of HIV-related and non-HIV-related clinical events, as well as continued chemo-prophylaxis.
The authors acknowledge the staff of the Adult Infectious Disease Clinic for supporting the data collection and contributing data to IeDEA East Africa.
IeDEA East Africa: Participating sites – Samuel Ayaya, Lameck Diero, Edwin Sang, Elyne Rotich, AMPATH, Eldoret, Kenya; Elizabeth Bukusi, Medical Research Institute, Kisumu, Kenya; Geoffrey R. Somi, National AIDS Control Program, Dar es Salaam, Tanzania; Rita Lyamuya, Morogoro Regional Hospital, Morogoro, Tanzania; Edward Lugina, Ocean Road Cancer Institute, Dar es Salaam, Tanzania; Mark Urassa, Denna Michael Mkwasa, Kapella Ngonyani, National Institute for Medical Research, Dar es Salaam, Tanzania; Andrew Kambugu, Tumbi Regional Hospital, Kibaha, Tanzania; Philippa Easterbrook, Andrew Kambugu, Marion Achieng-Kariuki, Infectious Diseases Institute, Kampala, Uganda; Fred Nalugoda, Rakai Health Sciences Program, Kalisizo, Uganda; John Ssali, Masaka Regional Referral Hospital, Masaka, Uganda; Mwebesa Bosco Bwana, Winnie Muyindike, Mbarara University of Science and Technology, Mbarara, Uganda. Regional Data Centre: Constantin T. Yiannoutsos (principle investigator), Beverly S. Musick, Yee Yee H. Kuhn, Indiana University, Indianapolis, Indiana, USA. In addition, the authors acknowledge support from a Wellcome Trust Uganda doctoral and postdoctoral fellowships in Infection and Immunity held by Agnes Kiragga and Damalie Nakanjako respectively, funded by a Wellcome Trust Strategic Award, grant number 084344. Special acknowledgement goes to the study participants (IDI friends), staff and patients from the sites that contributed data; in Uganda, Mbarara and Masaka; in Kenya, Academic Model Providing Access to Healthcare (AMPATH) sites and Family AIDS Care and Education Services (FACES); and in Tanzania, Ocean Road Cancer Institute (ORCI).
Authors’ contributions: D.N., A.K., A.K.D., and P.E. made substantial contribution to the conception, design, and data interpretation. A.K. and C.Y. made substantial contribution to the data analysis. D.N. drafted the manuscript. A.K.D., L.D., P.O., E.L., J.C. made substantial contribution to data collection at the sites that contributed data. B.M., K.W. and C.Y. made substantial contribution to the compilation of the IeDEA dataset and analysis methods. All authors read and approved the final manuscript for publication.
Competing interests: The authors declare that they have no competing interests.
Conflicts of interest
The authors have no conflicts of interest.
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