While highly active combination antiretroviral therapy (HAART) dramatically reduces morbidity and mortality due to AIDS [1,2], these benefits critically depend on patients achieving and maintaining high levels of medication adherence. Missing more than 5–10% of doses is linked to incomplete suppression of viral replication, declining CD4 cell counts [3–5] clinical progression to AIDS or death [3,6–8], and the development and spread of antiretroviral drug-resistant HIV [9–13]. Just as human behavior is the key to preventing HIV infection, behavior is arguably the most important determinant of successful treatment outcomes [3,5–8,14,15].
The unprecedented multilateral support through the President's Emergency Plan for AIDS Relief (PEPFAR) and the Global Fund to Fight AIDS, TB and Malaria (GFATM) are necessary to alleviate structural barriers to treatment in low resource countries and to expand access to essential drugs. However, even if all structural barriers to HAART are removed, HAART programs can still fail if they do not adequately address behavioral factors influencing adherence. Notwithstanding several encouraging reports on African populations [5,16,17], recent reports show that HAART adherence and clinical success rates vary widely across sub-Saharan programs, and offer no justification for complacency at this stage in our response to the global HIV/AIDS pandemic.
The challenge of measuring adherence
Medication adherence research from developed nations makes clear how difficult adherence is to measure accurately. In the absence of directly observed therapy, levels of adherence can only be estimated by use of surrogate measures. Commonly used methods include pill counts, pharmacy refill records, drug level monitoring, electronic drug monitors (EDM), and various self-reporting tools, such as questionnaires and visual analog scales. Each method has clear advantages and disadvantages (Table 1).
Knowledge of the comparative accuracy of different surrogate measures is based mainly on research conducted in developed countries over the past decade. Arnsten et al. reported mean HAART adherence rates of 79% by self-report but only 53% by EDM. Moreover, patients whose EDM data indicated high adherence (above 90%) were far more likely to achieve undetectable viral load (UDVL) than patients self-reporting the same level of adherence . Liu et al. concurrently compared several measures against patient UDVL rates . Mean adherence using EDM was 63% versus 83% for pill count and 93% for self-report. However, among patients who failed to achieve UDVL at 8 weeks, mean adherence was 87% for self-report, 74% for pill count, but only 59% for EDM. In both these studies, the poor association between self-report or pill counts and UDVL – compared with the relationship between EDM and UDVL – implied that they greatly overestimated true adherence. Similarly, a recently validated self-report instrument achieved 72% sensitivity and 91% specificity for detecting good (above 90%) adherence using EDM as the reference standard . A simple interpretation of this finding is that skepticism is warranted when patients report high adherence, though patients should generally be believed when reporting poor adherence.
Trials of directly observed HAART provide additional evidence of the accuracy of EDM. Since adherence can be known precisely, the link between adherence levels and UDVL can be established with a high degree of confidence. One trial studied the effectiveness of azidothymidine/lamivudine/abacavir among HIV infected prisoners. Mean adherence was 94% with 85% of inmates achieving UDVL . These results are remarkably similar to the relationship between UDVL and EDM-rated adherence: Paterson et al. observed UDVL in 80% of those with above 95% adherence,  while Arnsten et al. found UDVL in 78% of those with above 90% adherence .
These observations allow us to construct an approximate hierarchy of adherence measures, with physician assessment and self-report being least accurate, pill counts intermediate, and EDM the most accurate surrogate adherence marker. At least in developed country cohorts, self-report and pill count appear to greatly exaggerate actual adherence rates. Whether this hierarchy holds true for resource-poor country populations is currently unknown.
What is known about HAART adherence in Africa?
One of the earliest reports found high (above 90%) mean self-reported adherence and relatively high proportions (71%) achieving UDVL . This attracted much attention in the scientific and lay press given earlier concerns about the feasibility of HAART in Africa . Notably, the New York Times responded with a headline reading ‘Africans Outdo US Patients in Following AIDS Therapy’ . However, the study's patients may not have represented a generalizable example as all were concurrently enrolled in ongoing randomized controlled trials, and would have benefited from the structural supports provided by the trial. Moreover, the analysis excluded the adherence data for 52 subjects (16% of the total) who abandoned HAART before completing 48 weeks of follow up. Average adherence for the overall group would certainly have been lower had these subjects been included.
That said, several more recent reports of African HAART programs, most of which were not part of clinical trials, also reported high levels of adherence. In general, most relied on self-reported adherence, followed small numbers of patients for short periods, or were cross-sectional analyses and thus could not comment on sustained adherence rates (see Table 2).
However, a growing number of programs have now reported mediocre or poor adherence, and in the few studies that reported longitudinal data, declining adherence over time (Table 2). In Senegal, Laurent et al. noted that over 95% of their patients had adherence exceeding 80% after 1 month on therapy, but 18 months later only 80% of patients remained above that level. Concurrently, the proportion of their patients with UDVL fell from 79.6 to 59.3% . In Cameroon, Akam reported that mean self-reported adherence was initially only 68% and declined further over time .
Few studies compared multiple surrogate measures in parallel. Oyugi et al. measured adherence via self-report, pill count, visual analog score, and EDM, and found adherence levels at 24 weeks of 85, 86, 88, and 82%, respectively, implying a high degree of concordance between the various measures, and leading to speculation that the relationship between EDM and self-reported adherence in African cohorts might be tighter than was seen in US studies . However, these rates only applied to the 46% (32/70) of their participants who completed 24 weeks of observation, and the investigators only reported aggregate UDVL rates. In contrast, Omes et al. reported highly discordant levels of adherence between two forms of self-report: questionnaire and visual analog scale . Neither study provided data on which surrogate marker best predicted UDVL, therefore precluding conclusions about their relative accuracy. In studies that did report both UDVL and measured adherence, the association was frequently poor. Eholié et al. in Côte d’Ivoire reported that 52% of their patients were poorly adherent, and that HIV was often detectable even among those reporting over 90% adherence . A report from Durban, South African was perhaps most striking: with 100% of patients self-reporting 100% adherence, only 57% actually achieved UDVL  — a result highly reminiscent of US studies showing a significant disconnect between self-reported adherence and clinical success [18,19].
Where do we go from here?
Several observations emerge. First, reports that generalize about ‘adherence rates in Africa’ should be interpreted cautiously. A safer conclusion would be that adherence is proving to be highly challenging in African cohorts — just as it has for patients living in North America or Europe. We also question whether publication bias might lead results from less successful programs to go un-reported. Second, given growing doubts about the accuracy of self-reported adherence, some programs which appear to be successful may, in fact, be less so. Our interpretation of the limited data, notably those studies showing high self-reported adherence but low attainment of UDVL, [29,30] is that self-report is proving to be as unreliable a measure of adherence in Africa as it has elsewhere [18,19]. Third, external multinational funds should be allocated to supporting and studying adherence, and should not stop merely at the provision of test kits, basic training, and medications. Fourth, assuming successful models of adherence support can be found, it is uncertain whether they can be sustained with the often-limited support available from the public sector in many sub-Saharan countries. Notably, three of the lowest performing programs all appeared to have received little external technical or financial support through collaborations with foreign investigators or aid agencies. In contrast, the well-supported Médecins Sans Frontières (MSF) programs all included comprehensive adherence support mechanisms, and were among the most successful in terms of high reported adherence, low default rates, and high proportions of patients with UDVL. It would be extremely valuable to learn what aspects of MSF's adherence structures could be adapted cost-effectively and at scale in other settings.
These reports also help focus the research agenda for coming years. First and foremost, qualitative research into the behavioral reasons for patient non-adherence is urgently needed. The African adherence studies to date have all limited their scope to reporting adherence rates and occasionally population-level risk factors for non-adherence. Unfortunately, while epidemiologic studies are helpful at identifying ‘Who is non-adherent?’ they provide less insight into the more pressing question of ‘Why?’ a given patient chooses to adhere or not. Similarly, once a sufficient level of adherence is achieved, what are the behavioral factors that foster sustained adherence? Second, for programmatic evaluation, it is important to determine the most accurate and cost-effective approach to measuring adherence in African populations. To provide a common point of comparison between studies and populations, we feel strongly that the relative accuracy of surrogate adherence measures should always be indexed against an external clinical gold standard. UDVL may be best suited for this role, though rising rates of resistance and other factors could lead to an underestimation of adherence rates over time. Another option would be drug level monitoring, though operationalizing this would no doubt prove enormously challenging.
We have learned much over the past decades about treating HIV infection in developed settings. However, because of the demanding and unforgiving nature of the disease and our dependence on human behavior to take these highly effective medications, it is essential that we both truly understand the local complexities of adherence behavior and can respond to it effectively. It is important that the scope of programs funded by large multinational programs (PEPFAR, GFATM) support investigation of these issues within the context of existing and future programs.
C.J. Gill notes that support for his work on this paper was provided through NIH/NIAID K23 AI62208 01. Additional support was provided through the US Agency for International Development. Neither funder played any role in this article's design or had any input into its content, which does not necessarily reflect their views.
1. Palella FJ Jr, Delaney KM, Moorman AC, Loveless MO, Fuhrer J, Satten GA, et al
. Declining morbidity and mortality among patients with advanced human immunodeficiency virus infection. HIV Outpatient Study Investigators. N Engl J Med 1998; 338:853–860.
2. Hogg RS, Yip B, Kully C, Craib KJ, O'Shaughnessy MV, Schechter MT, et al
. Improved survival among HIV-infected patients after initiation of triple-drug antiretroviral regimens. CMAJ 1999; 160:659–665.
3. Paterson DL, Swindells S, Mohr J, Brester M, Vergis EN, Squier C, et al
to protease inhibitor therapy and outcomes in patients with HIV infection. Ann Intern Med 2000; 133:21–30.
4. Gross R, Bilker WB, Friedman HM, Strom BL. Effect of adherence
to newly initiated antiretroviral therapy
on plasma viral load. AIDS 2001; 15:2109–2117.
5. Orrell C, Bangsberg DR, Badri M, Wood R. Adherence
is not a barrier to successful antiretroviral therapy
in South Africa
. AIDS 2003; 17:1369–1375.
6. Van Dyke RB, Lee S, Johnson GM, Wiznia A, Mohan K, Stanley K, et al
. Reported adherence
as a determinant of response to highly active antiretroviral therapy
in children who have human immunodeficiency virus infection. Pediatrics 2002; 109:e61.
7. Bangsberg DR, Hecht FM, Charlebois ED, Zolopa AR, Holodniy M, Sheiner L, et al
to protease inhibitors, HIV-1 viral load, and development of drug resistance in an indigent population. AIDS 2000; 14:357–366.
8. Hogg RS, Heath K, Bangsberg D, Yip B, Press N, O'Shaughnessy MV, et al
. Intermittent use of triple-combination therapy is predictive of mortality at baseline and after 1 year of follow-up. AIDS 2002; 16:1051–1058.
9. Hertogs K, Bloor S, Kemp SD, Van den Eynde C, Alcorn TM, Pauwels R, et al
. Phenotypic and genotypic analysis of clinical HIV-1 isolates reveals extensive protease inhibitor cross-resistance: a survey of over 6000 samples. AIDS 2000; 14:1203–1210.
10. Pillay D. The emergence and epidemiology of resistance in the nucleoside-experienced HIV-infected population. Antivir Ther 2001; 6 Suppl 3:15–24.
11. Hecht FM, Grant RM, Petropoulos CJ, Dillon B, Chesney MA, Tian H, et al
. Sexual transmission of an HIV-1 variant resistant to multiple reverse-transcriptase and protease inhibitors. N Engl J Med 1998; 339:307–311.
12. Yerly S, Kaiser L, Race E, Bru JP, Clavel F, Perrin L. Transmission of antiretroviral-drug-resistant HIV-1 variants. Lancet 1999; 354:729–733.
13. Siegrist CA, Yerly S, Kaiser L, Wyler CA, Perrin L. Mother to child transmission of zidovudine-resistant HIV-1. Lancet 1994; 344:1771–1772.
14. Howard AA, Arnsten JH, Lo Y, Vlahov D, Rich JD, Schuman P, et al
. A prospective study of adherence
and viral load in a large multi-center cohort of HIV-infected women. AIDS 2002; 16:2175–2182.
15. Arnsten JH, Demas PA, Grant RW, Gourevitch MN, Farzadegan H, Howard AA, et al
. Impact of active drug use on antiretroviral therapy adherence
and viral suppression in HIV-infected drug users. J Gen Intern Med 2002; 17:377–381.
16. Muganzi AM, Bondo MC, Draru J, Biryeri J. Adherence to HAART in a arural resource lmited country HIV/AIDS treatment program: The experience of Arua Anti-Retroviral (ARV) Treatment Program-Uganda.XV International AIDS Conference
. Bangkok, Abstract: WePeB5760, March 30-April 2, 2004.
17. Darder M, Michaels D, Boulle A, Ncobo M, MacLean E, Goemaere E. Determinants of short and long-term adherence to antiretroviral treatment in resource-poor settings.XV International AIDS Conference
. Bangkok, Abstract: B11852, March 30-April 2, 2004.
18. Arnsten JH, Demas PA, Farzadegan H, Grant RW, Gourevitch MN, Chang CJ, et al
. Antiretroviral therapy adherence
and viral suppression in HIV-infected drug users: comparison of self-report and electronic monitoring. Clin Infect Dis 2001; 33:1417–1423.
19. Liu H, Golin CE, Miller LG, Hays RD, Beck CK, Sanandaji S, et al
. A comparison study of multiple measures of adherence
to HIV protease inhibitors. Ann Intern Med 2001; 134:968–977.
20. Knobel H, Alonso J, Casado JL, Collazos J, Gonzalez J, Ruiz I, et al
. Validation of a simplified medication adherence
questionnaire in a large cohort of HIV-infected patients: the GEEMA Study. AIDS 2002; 16:605–613.
21. Kirkland LR, Fischl MA, Tashima KT, Paar D, Gensler T, Graham NM, et al
. Response to lamivudine-zidovudine plus abacavir twice daily in antiretroviral-naive, incarcerated patients with HIV infection taking directly observed treatment. Clin Infect Dis 2002; 34:511–518.
22. Harries AD, Nyangulu DS, Hargreaves NJ, Kaluwa O, Salaniponi FM. Preventing antiretroviral anarchy in sub-Saharan Africa
. Lancet 2001; 358:410–414.
23. McNeil DGJ. Africans Outdo U.S. Patients in Following AIDS Therapy. New York TImes
24. Laurent C, Diakhate N, Gueye NF, Toure MA, Sow PS, Faye MA, et al
. The Senegalese government's highly active antiretroviral therapy
initiative: an 18-month follow-up study. AIDS 2002; 16:1363–1370.
25. Akam AWC. Anti-retroviral adherence in a resource poor setting.XV International AIDS Conference
. Bangkok, March 30-April 2, 2004.
26. Oyugi JH, Byakika-Tusiime J, Ragland K, Mugyenyi P, Kityo C, Mugerwa RD, et al
. Treatment outcomes and adherence to generic Triomune and Maxivir therapy in Kampala, Uganda.XV International AIDS Conference
. Bangkok, Abstract: WeORB1323, March 30-April 2, 2004.
27. Omes C, Schuman M, Kamesigwa J, EDemeester R, Mukakalisa J, Parisel A, et al
. Adherence to antiretroviral (ARV) therapy among advanced-stage, indigent patients in the funded ESTHER programme in Kigali, Rwanda.XV International AIDS Conference
. Bangkok, Abstract: B12315, March 30-April 2, 2004.
28. Eholie ESP, Bissagnene-Emmanuel BE, Ouiminga-Maryam OM, Kangah-Koffi KC, Diakhite DN, Ehui EE, et al
. Adherence to HAART and its principal determinants in the HIV infected adults in Abidjan (Cote d’Ivoire).XV International AIDS Conference
. Bangkok, Abstract: WePeB5790, March 30-April 2, 2004.
29. Brown S, Friedland GH, Bodasing U. Assessment of adherence to antiretroviral therapy in HIV-infected South African adults.XV International AIDS Conference
. Bangkok, Abstract: B12223, March 30-April 2, 2004, 2004.
30. Shihab HM, Mwesigire D, Ronald A, Kamya MR, Mayanja B, Spacek LA, et al
. Response to antiretroviral therapy (ART) in the resource-limited setting (RLS) of Mulago Hospital AIDS Clinic (MHAC) in Kampala, Uganda.IDSA
. Boston, Abstract 902, 2004.
31. Wagner JH, Justice AC, Chesney M, Sinclair G, Weissman S, Rodriguez-Barradas M. Patient- and provider-reported adherence
: toward a clinically useful approach to measuring antiretroviral adherence
. J Clin Epidemiol 2001; 54 Suppl 1:S91–S98.
32. Gross R, Bilker WB, Friedman HM, Coyne JC, Strom BL. Provider inaccuracy in assessing adherence
and outcomes with newly initiated antiretroviral therapy
. AIDS 2002; 16:1835–1837.
33. Haubrich RH, Little SJ, Currier JS, Forthal DN, Kemper CA, Beall GN, et al
. The value of patient-reported adherence
to antiretroviral therapy
in predicting virologic and immunologic response. California Collaborative Treatment Group. AIDS 1999; 13:1099–1107.
34. Barsky AJ. Forgetting, fabricating, and telescoping: the instability of the medical history. Arch Intern Med 2002; 162:981–984.
35. Murri R, Ammassari A, Gallicano K, De Luca A, Cingolani A, Jacobson D, et al
. Patient-reported nonadherence to HAART
is related to protease inhibitor levels. J Acquir Immune Defic Syndr 2000; 24:123–128.
36. Maher K, Klimas N, Fletcher MA, Cohen V, Maggio CM, Triplett J, et al
. Disease progression, adherence
, and response to protease inhibitor therapy for HIV infection in an Urban Veterans Affairs Medical Center. J Acquir Immune Defic Syndr 1999; 22:358–363.
37. Brundage RC, Yong FH, Fenton T, Spector SA, Starr SE, Fletcher CV. Intrapatient variability of efavirenz concentrations as a predictor of virologic response to antiretroviral therapy
. Antimicrob Agents Chemother 2004; 48:979–984.
38. Nwokike J. Baseline data and predictors of adherence in patients on antiretroviral therapy in Maun General Hospital, Botswana.ICIUM
. Bangkok, Abstract HI012, 2004.
39. Traore AA, Nguyen VK, McCarrick P, Dhaliwal M, Tioendrebeogo I, Ilboudo A. Barriers to adherence to ARV therapy in a community-based cohort in Burkina Faso.XV International AIDS Conference
. Bangkok, Abstract WePeB5824, March 30-April 2, 2004.
40. Byakika-Tusiime J, Oyugi JH, Tumwikirize WA, Katabira ET, Mugyeni PN, Bangsberg DR. Ability to purchase and secure stable therapy are significant predictors of non-adherence to antiretroviral therapy in Kampala, Uganda.10th Conference on Retroviruses and Opportunistic Infections
. Boston, Abstract 170, February 10–14, 2003.
41. Ferris DC, Dawood H, Chiasson MA, Diamond B, Hammer SM, Lalloo UG. Self-reported adherence to antiretroviral therapy and virologic outcomes in HIV-infected persons in Durban, KwaZulul Natal, South Africa.XV International AIDS Conference
. Bangkok, Abstract: WePeB5829, March 30-April 2, 2004.
42. Daniel OJ, Ogun SA, Odusoga OL, Falola RL, Ogundahunsi OA, Salako AA, et al
. Adherence pattern to ARV drugs among AIDS patients on sef-purcased drugs and those on free medications in Sagamu, Nigeria.XV International AIDS Conference
. Bangkok, March 30-April 2, 2004.
43. Tu D, Kos N, Culbert H, Migabo K, Amisi T. ARV selection criteria and innovative group adherence counseling in Bukavu, Democratic Republic of Congo – Program implementation in the context of chronic war and a failing healthcare system.XV International AIDS Conference
. Bangkok, Abstract: B12702, March 30-April 2, 2004.
44. Gialloreti LE, DeLuca A, Perno CF, Liotta G, Narcisco P, Abdel Magid N, et al
. Increase in survival in HIV-1 infected subjects in Matola, Mozambique, after the introduction of combination therapy with generic manufactured antiretrovirals; Preliminary results from the DREAM cohort.10th Conference on Retroviruses and Opportunistic Infections
. Boston, Abstract 175, February 10–14, 2004.