Secondary Logo

Journal Logo

Early mortality among adults accessing a community-based antiretroviral service in South Africa: implications for programme design

Lawn, Stephen Da,c; Myer, Landona,b,d; Orrell, Catherinea; Bekker, Linda-Gaila; Wood, Robina

doi: 10.1097/01.aids.0000194802.89540.e1

Objectives: To determine rates, risk factors and causes of death among patients accessing a community-based antiretroviral treatment (ART) programme both prior to and following initiation of treatment.

Methods: All in-programme deaths were ascertained between September 2002 and March 2005 among treatment-naive patients enrolled into a prospective community-based ART cohort in Cape Town, South Africa.

Results: Of 712 patients (median CD4 cell count, 94 cells/μl), 578 (81%) started triple ART a median of 29 days after enrolment. 68 (9.5%) patients died during 563 person-years of observation. The high pretreatment mortality rate of 35.6 deaths/100 person-years [95% confidence interval (CI), 23.0–55.1) decreased to 2.5/100 person-years (95% CI, 0.9–6.6) at 1 year among those who received ART. However, within the first 90 days from enrolment, 29 of 44 (66%) deaths occurred among patients awaiting ART; these would not be identified by an on-treatment analysis. Multivariate analysis showed that risk of death (both pre-treatment and on-treatment) was independently associated with baseline CD4 cell count and World Health Organization (WHO) clinical stage; stage 4 disease was the strongest risk factor. Major attributed causes of death were wasting syndrome, tuberculosis, acute bacterial infections, malignancy and immune reconstitution disease.

Conclusions: Most early in-programme deaths occurred among patients with advanced immunodeficiency but who had not yet started ART. Programme evaluation using on-treatment analyses greatly underestimated early mortality. This mortality would be reduced by minimizing unnecessary in-programme delays in treatment initiation and by starting ART before development of WHO stage 4 disease.

From the aThe Desmond Tutu HIV Centre, Institute for Infectious Disease and Molecular Medicine and

bInfectious Diseases Epidemiology Unit, School of Public Health and Family Medicine, University of Cape Town, Cape Town, South Africa

cClinical Research Unit, Department of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK

dDepartment of Epidemiology, Mailman School of Public Health, Columbia University, New York, USA.

Received 17 July, 2005

Revised 17 August, 2005

Accepted 24 August, 2005

Correspondence to Dr S.D. Lawn, Desmond Tutu HIV Centre, Institute of Infectious Disease and Molecular Medicine, Faculty of Health Sciences, University of Cape Town, Anzio Road, Observatory 7925, Cape Town, South Africa. E-mail:

Back to Top | Article Outline


While there is ample evidence that use of antiretroviral treatment (ART) dramatically improves the prognosis of individuals with HIV infection [1–4], the vast majority of those requiring ART in sub-Saharan Africa and other resource-limited settings do not have access to this treatment. To address these inequities in treatment availability, a number of initiatives have been developed to expand ART access [5]. The collective goal of these initiatives under the umbrella of the World Health Organization (WHO) is to provide ART to 3 million people by the end of 2005 [5]. While progress towards this goal is being achieved, it was estimated that just 310 000 (< 8%) of the 4 million patients aged 15–49 years in sub-Saharan Africa who needed treatment were receiving it by the end of 2004 [6].

The huge number of patients requiring treatment presents a formidable logistical challenge. Despite increasing allocation of resources to expand access to ART in resource-limited settings, little is known about how best to deliver treatment services. It is becoming increasingly clear that the impact of ART services at a population level will primarily be determined not by issues of drug efficacy [7] but rather by programmatic issues of treatment availability, accessibility and delivery [8]. Data from existing ART programmes are urgently required to identify approaches to optimize outcomes. Previous studies indicate that the first-year mortality from the time of initiation of ART is broadly similar among cohorts receiving ART in low- and high-income countries [9–14]. The current study examines not only mortality during treatment but also that occurring in the interval between eligible individuals being enrolled into the ART programme and the actual initiation of ART. Identification of risk factors and stratification of mortality data according to enrolment characteristics has also permitted evaluation of treatment criteria for patients in low-resource settings.

Back to Top | Article Outline


Antiretroviral treatment programme

The ART service described here is based at the Gugulethu Community Health Centre in Nyanga district, Cape Town [15]. This peri-urban district is home to a predominantly African population of over 300 000, the vast majority of whom live in conditions of low socioeconomic status. In 2003, the antenatal HIV seroprevalence was 28%. Ten primary care HIV clinics form the patient referral base and enrolment into the ART programme follows the Department of Health's national guidelines [16], which are based on the WHO recommendations (2002) [17]. These criteria include those with a prior AIDS diagnosis (WHO stage 4 disease) or a blood CD4 cell count < 200 cells/μl.

Following referral to the ART service, the standard schedule of visits was as follows: screening visit (week 0), blood tests for plasma HIV load and blood CD4 lymphocyte count (week 2), treatment initiation (week 4) and treatment follow up (weeks 8, 12 and 20, and 16-weekly thereafter). At the screening visit, a treatment readiness evaluation was completed and a 4-week supply of co-trimoxazole was dispensed, with pill counts at 14 and 28 days to assess adherence. Patients were assessed by a doctor for symptomatic HIV-associated disease.

At the screening visit, patients were also allocated a therapeutic counsellor living in the same community whose role was to use clinic and home visits to provide ongoing counselling and adherence support. These counsellors provided weekly updates to the multidisciplinary team about the status of patients, including information regarding those who failed to attend follow up appointments [16]. The treatment readiness status of patients was reviewed each week until either treatment was started or the patient was permanently deferred or had died. Potential reasons for temporary deferral of treatment included current investigation of an intercurrent opportunistic infection, lack of patient readiness or a failure to attend follow-up appointments. Reasons for permanent deferral of patients either before or after commencing treatment included decision to access treatment elsewhere, recurrent failure to attend follow up clinic appointments, relocation out of area and psychosocial reasons such as denial of HIV infection status.

First-line ART comprised stavudine, lamivudine plus a non-nucleoside reverse transcriptase inhibitor (efavirenz or nevirapine). The second-line regimen for those failing the first-line treatment comprised lopinavir/ritonavir, zidovudine and didanosine. Treatment adherence and viral load suppression < 400 copies/ml in this cohort both exceed 90% at 1 year [18]. All treatment was free of charge and there were no interruptions in drug supply. All patients with CD4 cell counts < 200 cells/μl received daily co-trimoxazole prophylaxis; dapsone was used as an alternative. In addition to the scheduled clinic appointments, patients had open access to the clinic for medical problems. Patients requiring in-patient care were referred to a 200-bed secondary hospital nearby.

Back to Top | Article Outline

Data sources

Structured clinical records were maintained on all patients screened on entry to the ART programme and this information was transferred on a weekly basis to a database. Where blood CD4 cell counts and viral load measurements from the week 2 visit were missing, the results of tests done at the local referring centre within the 3 months prior to the screening visit were used where available.

Information regarding deaths of patients within the care of the ART clinic was obtained from the local secondary and tertiary care hospitals, hospital mortality review meetings and postmortem examinations. The most likely attributable cause of death of each patient was assigned based on all the available information after detailed review by two specialists in infectious diseases and HIV medicine.

Back to Top | Article Outline

Data analysis

Data were analysed using STATA version 8 (College Station, Texas, USA). Wilcoxon rank sum and Fisher's exact tests were used to compare medians and proportions, respectively. For the main analysis, person-time was calculated from the date of initial screening by the service until the earliest of the following dates: (a) permanent deferral from the ART service; (b) death, or (c) date of data censorship (March 2005) for those alive and still enrolled into the programme. Stratified analyses were used to compare mortality rates by 90-day intervals after enrolment into the programme, WHO stage, baseline CD4 cell count, and for person-time while receiving and or not receiving ART. Additional analyses were restricted to individuals receiving ART, using person-time calculated from the date of ART initiation until death, permanent deferral or censorship of the dataset. Kaplan–Meier analyses with log rank tests were used to examine the effect of patient characteristics on survival probabilities. All rates are reported per 100 person-years and all statistical tests were two sided at α = 0.05.

Multivariate analyses modelled the association between mortality rate, treatment status (based on person-time in the programme while receiving or not receiving ART), WHO clinical stage and CD4 cell count at screening, and the age and gender of the participants. To account for intraindividual correlations (on and off treatment) a population-average log-linear model was used with an exchangeable working correlation structure and sandwich (robust) estimators. The results are presented as mortality rate ratios with corresponding 95% confidence intervals (CI).

Back to Top | Article Outline


Enrolment and follow up

Between September 2002 and February 2005, 758 individuals were referred for ART. Of these, the following were excluded from the study analysis: patients < 18 years of age (n = 16); those transferred into the ART service having previously initiated treatment elsewhere (n = 6) and those ineligible for ART according to programme criteria (n = 24). The remaining 712 subjects were included in this analysis. Of these, 527 (74%) were female and the median age was 33 years [interquartile range (IQR), 28.5–38]. Baseline blood CD4 lymphocyte counts and plasma viral load measurements were available for 675 (95%) and 647 (91%) of subjects, respectively. The median blood CD4 lymphocyte count was 94 cells/μl; the numbers of patients with CD4 cell counts < 50, 51–100, 101–150 and > 151 cells/μl were 187 (28%), 163 (24%), 152 (23%) and 173 (26%), respectively. The median plasma viral load was 72 349 copies/ml (IQR, 30 721–191 000). Disease was categorized as WHO clinical stage 1 for 63 subjects (9%), stage 2 for 78 (11%), stage 3 for 354 (50%) and stage 4 for 215 (30%); data were not recorded for two subjects (0.3%).

After screening, 578 patients (81%) started ART. The median interval between screening and initiation of treatment was 29 days: 75% of patients started treatment within 6 weeks (42 days) and 96% within 3 months (90 days). The length of this interval was not associated with blood CD4 cell count or viral load. A total of 563 person-years of observation accrued during follow-up, of which 488 person-years were during ART, and the median period of observation during treatment was 284 days (IQR, 124–510) with a maximum of 925 days (2.5 years). Twenty-two treated patients (4%) were lost to follow up through transfer to another programme (n = 3) or failure to attend follow-up appointments (n = 19; 3%).

Among 134 patients (19%) who did not receive ART, the most frequent reasons for this were death, decision to access treatment elsewhere, failure to attend follow up clinic appointments, moving out of the area and psychosocial reasons such as denial of HIV infection status. The median period of observation for these patients was 28 days (IQR, 19–50; maximum, 125 days). The total untreated patient time was 75 person-years and was made up of that for patients who did not receive ART as well as that for patients who subsequently received ART.

Back to Top | Article Outline

Death rates

Sixty eight (9.5%) patients died following enrolment into the programme, with an all-cause mortality rate of 12.1 deaths/100 person-years (95% CI, 9.5–15.3) (Table 1). The baseline pretreatment mortality rate (during the first 30 days of entry to the programme) was very high (35.6 deaths/100 person-years; 95% CI, 23.0–55.1) but the overall rate decreased markedly during follow up (Table 1). Forty-four (65%) of the deaths occurred within the first 90 days from enrolment. Among those who received ART, the mortality rate during the first month of treatment (17.5 deaths/100 person-years, 95% CI, 8.8–35.0) was 2.03-fold (95% CI, 0.93–5.79) lower than the baseline rate. The mortality rate continued to decrease during ART, and after 6–9 months the rate was 13.2-fold lower than the baseline rate. The survival probability among treated patients at 1 year was 0.929 (Fig. 1). Deaths among patients who did not start ART was very high (Fig. 2; Table 1) and 31 patients (5.4% of enrolled patients) died before they were able to start ART. Most importantly, among the 44 patients who died within 3 months of enrolment, 29 (66%) were not receiving ART and would have been excluded from data evaluating the programme by an on-treatment analysis.

Table 1

Table 1

Fig. 1

Fig. 1

Fig. 2

Fig. 2

Back to Top | Article Outline

Risk factors for mortality

It was hypothesized that the very high early mortality rate was primarily related to enrolment of patients with very advanced immunodeficiency; therefore, the relationship was examined between survival probability and baseline WHO clinical stage of disease or the blood CD4 cell count. Among those who received ART, no deaths occurred among those with stage 1 or 2 disease; in contrast, patients with stage 3 and stage 4 disease had an incrementally greater risk of death (Fig. 3a). Increasing risk of death was also significantly associated with decreasing baseline CD4 cell count (Fig. 3b). Similar significant associations were seen among those who did not receive ART (data not shown). Among all patients enrolled into the programme, the median blood CD4 cell count of those who died was lower than that of those who survived (54 versus 98 cells/μl; P < 0.001). Furthermore, patients who died were more likely to have stage 4 disease than those who did not die (37/68 [54%] versus 178/644 [28%]; P < 0.0001).

Fig. 3

Fig. 3

Kaplan–Meier survival curves for all patients enrolled into the programme show that stage 4 disease and baseline blood CD4 cell count ≤ 50 cells/μl were both associated with a substantially lower survival probability compared with other patients (Fig. 3c,d). Among the 44 deaths that occurred within the first 3 months of the programme, 35 (66%) had stage 4 disease and 22 (50%) had blood CD4 cell counts < 50 cells/μl. Overall, patients with stage 4 disease and/or blood CD4 cell counts < 50 cells/μl accounted for 80% of the deaths within 3 months of programme entry. In contrast, patients with CD4 cells counts > 150 cells/μl had a low risk of death (Fig. 3d).

Having adjusted for the effects of treatment, multivariate analysis showed that the mortality rate was not independently associated with age or sex but was associated with disease stage and blood CD4 cell count. Compared with patients with stages 1 and 2 disease, those with stage 3 disease and stage 4 disease had mortality rate ratios of 3.44 (95% CI, 0.80–14.85) and 5.93-fold (95% CI, 1.36–25.89), respectively. Similarly, the mortality rate ratio comparing those with CD4 cell counts < 50 and > 50 cells/μl was 3.34 (95% CI, 1.31–8.50).

Back to Top | Article Outline

Cause of death

Likely causes were identified for 61 of the 68 (89.7%) deaths. Postmortem examinations were carried out for six patients. Almost two-thirds of deaths were attributable to wasting syndrome, tuberculosis, acute bacterial infections and malignancy (Table 2). ART was associated with a smaller proportion of deaths from acute respiratory infections even though antibiotic prophylaxis was received by all patients both before and during ART. Of particular note, six cases of microbiologically proven cryptococcal meningitis occurred, all among patients within the initial weeks of ART. Of these, four were receiving secondary prophylaxis with fluconazole. The temporal association between initiation of ART and development of fulminant cryptococcal meningitis strongly implicated immune reconstitution disease as a cause for this presentation. Three other deaths among patients receiving ART were also thought to be related to immune reconstitution disease, including two associated with tuberculosis and one with Kaposi's sarcoma. Of these, two were diagnosed by postmortem examination. Overall, immune reconstitution disease was thought to have contributed to 9 of the 37 (24%) deaths during ART. Among three drug-related deaths (Table 2), two were among patients receiving ART: one patient developed nevirapine-induced skin rash complicated by septicaemia and another receiving nucleoside analogue reverse transcriptase inhibitors developed laboratory-confirmed lactic acidosis.

Table 2

Table 2

Back to Top | Article Outline


This study defined mortality rates among patients accessing a community-based public sector ART programme in South Africa and who were eligible for treatment under the WHO 2002 guidelines [17]. This is the first study in a resource-limited setting to report not only mortality rates among patients during ART but also rates in the interval between enrolment into the programme and the actual start of treatment. Our data highlight substantial ‘unseen’ in-programme mortality that occurs within the interval between enrolment into the programme and initiation of ART, providing important additional insights beyond those provided by previous studies reported from sub-Saharan Africa [9–14]. Furthermore, we identified causes of death among the majority of patients and were able to determine the mortality risk associated with differing levels of baseline immunodeficiency, thereby providing an evaluation of ART enrolment criteria. These analyses were made possible by rigorous prospective data collection. Use of community-based therapeutic counsellors allocated to every patient greatly enhanced the data completeness and assignment of outcomes for patients who failed to attend follow up appointments. Since triple-drug ART and prophylactic co-trimoxazole were provided free of charge to all patients, data were not limited by a variable standard of care based upon the financial resources of the patients.

The baseline death rate among patients enrolled into the programme was extremely high. Following development of AIDS, the median survival of untreated patients in South Africa and rural Uganda is just 9–10 months [19,20] compared with around 2 years in high-income countries prior to the advent of ART [21–23]. A collaborative analysis of datasets from cohorts receiving ART in northern and southern hemisphere countries also shows that early on-treatment mortality rates among patients with advanced baseline immunodeficiency were much higher in low-income countries than in high-income countries despite similar virological and immunological responses to treatment [24].

A substantial reduction in mortality associated with ART was evident within the first months of treatment and the probability of survival on treatment at 1 year was high (0.929). However, our most important finding was that 66% of the patients who died within 90 days of enrolment to the programme were not yet receiving ART. The interval from enrolment to starting treatment in this study (median, 29 days; 75th centile, 42) was short compared with the minimum of 4 months lead-in time at a similar community-based antiretroviral programme in South Africa [9] and is likely to compare favourably with many programmes in the region. The pretreatment interval in this programme permitted clinical assessment, blood testing, patient attendance at a structured education programme, arrangement of a home assessment by the therapeutic counsellor, assessment of treatment compliance using co-trimoxazole pill counts and procurement of drug. Thorough preparation of patients for treatment in this way has been associated with very high treatment compliance rates and excellent virological response rates [18,25].

An important implication of this study is that careful consideration needs to be given to the design of community-based ART programmes for low-income countries. Although it cannot be concluded from the data here, minimization of the in-programme pretreatment interval may well decrease mortality in this and other programmes. However, a balance needs to be established between minimizing the pretreatment interval (potentially reducing early mortality risk) and allowing adequate time to prepare patients for treatment (promoting high rates of treatment adherence and reducing long-term mortality rates). A system might also be employed whereby patients at highest risk of death are ‘fast-tracked’ onto treatment; such patients might include those with stage 4 disease, a blood CD4 lymphocyte count < 50 cells/μl or an AIDS-defining illness associated with a particularly poor prognosis, such as wasting syndrome [26,27]. Data from other ART services in resource-limited settings may help to identify optimal strategies. A further implication of these data is that failure to record in-programme pretreatment deaths may have resulted in survival bias in previous reports, leading to an overestimation of survival benefits among those with advanced immunodeficiency. Overestimation of the benefits of ART among such patients may unwittingly tend to skew priorities away from treating patients at an earlier stage of disease.

The extremely high mortality in the first 30 days from enrolment suggests that many patients enrolling into the programme had disease that was too far advanced at entry. This is clearly supported by the finding that risk of death was very strongly associated with baseline blood CD4 cell count and WHO clinical stage of disease. Indeed, 80% of deaths within the first 3 months from enrolment were among those with stage 4 disease or a baseline blood CD4 cell count of < 50 cells/μl. The South African ART roll-out programme currently employs the WHO 2002 guidelines, recommending treatment for those with a clinical criterion of stage 4 disease or a laboratory criterion of a CD4 cell count < 200 cells/μl. We found that in-programme mortality among those with CD4 cell counts > 151 cells/μl was low (Fig. 3d), suggesting that initiation of ART among patients with CD4 cells counts of 150–200 cells/μl would be an acceptable target range for initiating treatment based on mortality outcomes. In contrast, however, the in-programme mortality rate among those with stage 4 disease was unacceptably high (Fig. 3c). Once patients developed stage 4 disease, the mortality rate is already so high that the inevitable delays inherent in accessing care, diagnosis, referral to an ART programme, preparation for treatment and actually initiating ART result in an unacceptable mortality rate, of the order of 7% per month [19]. Based on these data, the clinical criterion for initiating ART should be when patients first develop symptomatic (stage 3) disease.

Tuberculosis is the most frequent manifestation of WHO stage 3 disease in the region and the tuberculosis treatment programmes could provide a key point of access to the ART programme. Therefore, recommending treatment for all patients with symptomatic (stage 3 and stage 4) disease and those whose CD4 cell counts < 200 cells/μl may reduce mortality. In the face of resource limitations, such a policy would avoid the even greater expansion of patient numbers requiring treatment that would result from recommendations to treat patients with CD4 cell counts < 350 cells/μl as is practice in high-income countries.

Cause-specific mortality data for HIV-infected individuals living in sub-Saharan Africa are lacking. Postmortem studies of selected in-patient deaths in Côte D'Ivoire and Botswana found that the predominant causes were tuberculosis, bacterial pneumonia and cerebral toxoplasmosis [28,29]. Active tuberculosis was also detected by postmortem examinations among nearly one half of patients dying with HIV wasting syndrome in West Africa [30]. In our cohort, in which prophylaxis with co-trimoxazole (or dapsone) was universally prescribed, 68% of deaths among patients not receiving HAART were associated with wasting syndrome, tuberculosis and acute bacterial infections. The most striking difference in mortality pattern, comparing those who did and did not receive ART, was that the six deaths from cryptococcal meningitis all occurred among patients within the first few weeks of ART, strongly suggesting immune reconstitution disease as a possible cause [31]. Overall immune reconstitution disease was thought likely to have contributed to over 20% of deaths within the first 3 months of ART. This is typically a complication of patients with advanced immunosuppression at the time ART is started and this phenomenon provides another argument favouring treatment of patients earlier in the course of disease.

In summary, this analysis found that most early in-programme deaths occurred among patients with advanced immunodeficiency who had not yet initiated ART. If this observation is shared by other programmes, then previously published programme evaluations using on-treatment analyses may have greatly underestimated early in-programme mortality. Unnecessary in-programme delays in treatment initiation should be minimized. In addition, we suggest that that the programmatic application of the WHO 2002 treatment guidelines is associated with an unacceptably high mortality rate in this setting. Strategies to reduce early mortality should include treatment of all patients with symptomatic (stage 3 and stage 4) disease.

Sponsorship: SDL is funded by the Wellcome Trust, London, UK with grant 074641/Z/04/Z. LM, CO, LGB and RW are all funded in part by the National Institutes of Health through a CIPRA grant 1U19AI53217–01.

Note: The authors have no conflicts of interest.

Back to Top | Article Outline


1. Brodt HR, Kamps BS, Gute P, Knupp B, Staszewski S, Helm EB. Changing incidence of AIDS-defining illnesses in the era of antiretroviral combination therapy. AIDS 1997; 11:1731–1738.
2. 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.
3. Detels R, Munoz A, McFarlane G, Kingsley LA, Margolick JB, Giorgi J, et al. Effectiveness of potent antiretroviral therapy on time to AIDS and death in men with known HIV infection duration. Multicenter AIDS Cohort Study Investigators. JAMA 1998; 280:1497–1503.
4. Egger M, May M, Chene G, Phillips AN, Ledergerber B, Dabis F, et al. Prognosis of HIV-1-infected patients starting highly active antiretroviral therapy: a collaborative analysis of prospective studies. Lancet 2002; 360:119–129.
5. World Health Organization. The 3 by 5 Initiative. Geneva: World Health Organization; accessed April 2005:
6. WHO/UNAIDS. ‘3 by 5’ Progress Report: December 2004. Geneva: WHO/UNAIDS; 2004. Accessed April 2005
7. Ivers LC, Kendrick D, Doucette K. Efficacy of antiretroviral therapy programs in resource-poor settings: a meta-analysis of the published literature. Clin Infect Dis 2005; 41:217–224.
8. Lawn SD, Myer L, Wood R. Efficacy of antiretroviral therapy in resource-poor settings: are outcomes comparable to those in the developed world?Clin Infect Dis 2005: 41: in press.
9. Coetzee D, Hildebrand K, Boulle A, Maartens G, Louis F, Labatala V, et al. Outcomes after two years of providing antiretroviral treatment in Khayelitsha, South Africa. AIDS 2004; 18:887–895.
10. Weidle PJ, Malamba S, Mwebaze R, Sozi C, Rukundo G, Downing R, et al. Assessment of a pilot antiretroviral drug therapy programme in Uganda: patients’ response, survival, and drug resistance. Lancet 2002; 360:34–40.
11. Laurent C, Ngom Gueye NF, Ndour CT, Gueye PM, Diouf M, Diakhate N, et al. Long-term benefits of highly active antiretroviral therapy in Senegalese HIV-1-infected adults. J Acquir Immune Defic Syndr 2005; 38:14–17.
12. Djomand G, Roels T, Ellerbrock T, Hanson D, Diomande F, Monga B, et al. Virologic and immunologic outcomes and programmatic challenges of an antiretroviral treatment pilot project in Abidjan, Côte d'Ivoire. AIDS 2003; 17(Suppl 3):S5–S15.
13. Tassie JM, Szumilin E, Calmy A, Goemaere E. Highly active antiretroviral therapy in resource-poor settings: the experience of Médecins sans Frontières. AIDS 2003; 17:1995–1997.
14. Laurent C, Kouanfack C, Koulla-Shiro S, Nkoue N, Bourgeois A, Calmy A, et al. Effectiveness and safety of a generic fixed-dose combination of nevirapine, stavudine, and lamivudine in HIV-1-infected adults in Cameroon: open-label multicentre trial. Lancet 2004; 364:29–34.
15. Bekker LG, Orrell C, Reader L, Matoti K, Cohen K, Martell R, et al. Antiretroviral therapy in a community clinic: early lessons from a pilot project. S Afr Med J 2003; 93:458–462.
16. South Africa National Department of Health. National Antiretroviral Treatment Guidelines. Pretoria: South African Ministry of Health; 2004.
17. World Health Organization. Scaling up Antiretroviral Therapy in Resource-limited Settings: Guidelines for a Public Health Approach; Executive Summary. Geneva: World Health Organization 2002. Accessed 15 April 2005:
18. Orrell C, Badri M, Wood R. Measuring adherence in a community setting: which measure most valuable?XVI International AIDS Conference Bangkok, July 2004 [abstract WePEB5787].
19. Badri M, Bekker LG, Orrell C, Pitt J, Cilliers F, Wood R. Initiating highly active antiretroviral therapy in sub-Saharan Africa: an assessment of the revised World Health Organization scaling-up guidelines. AIDS 2004; 18:1159–1168.
20. Morgan D, Mahe C, Mayanja B, Okongo JM, Lubega R, Whitworth JA. HIV-1 infection in rural Africa: is there a difference in median time to AIDS and survival compared with that in industrialized countries? AIDS 2002; 16:597–603.
21. Ghirardini A, Puopolo M, Rossetti G, Mancuso G, Perugini L, Piseddu G, et al. Survival after AIDS among Italian haemophiliacs with HIV infection. The Italian Group on Congenital Coagulopathies. AIDS 1995; 9:1351–1356.
22. Whitmore-Overton SE, Tillett HE, Evans BG, Allardice GM. Improved survival from diagnosis of AIDS in adult cases in the United Kingdom and bias due to reporting delays. AIDS 1993; 7:415–420.
23. Del Amo J, Petruckevitch A, Phillips A, Johnson AM, Stephenson J, Desmond N, et al. Disease progression and survival in HIV-1-infected Africans in London. AIDS 1998; 12:1203–1209.
24. Dabis.F, Schechter, M., Egger, M., for the ART-LINC/ART-CC Study Groups. Response to highly active retroviral therapy in low- and high-income countries: analysis from 4 continents.Twelvth Conference on Retroviruses and Opportunistic Infections. Boston, February 2005 [abstract 23].
25. 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.
26. Post FA, Badri M, Wood R, Maartens G. AIDS in Africa: survival according to AIDS-defining illness. S Afr Med J 2001; 91:583–586.
27. Morgan D, Malamba SS, Orem J, Mayanja B, Okongo M, Whitworth JA. Survival by AIDS defining condition in rural Uganda. Sex Transm Infect 2000; 76:193–197.
28. Lucas SB, Hounnou A, Peacock C, Beaumel A, Djomand G, N'Gbichi JM, et al. The mortality and pathology of HIV infection in a West African city. AIDS 1993; 7:1569–1579.
29. Ansari NA, Kombe AH, Kenyon TA, Hone NM, Tappero JW, Nyirenda ST, et al. Pathology and causes of death in a group of 128 predominantly HIV-positive patients in Botswana, 1997–1998. Int J Tuberc Lung Dis 2002; 6:55–63.
30. Lucas SB, de Cock KM, Hounnou A, Peacock C, Diomande M, Honde M, et al. Contribution of tuberculosis to slim disease in Africa. Br Med J 1994; 308:1531–1533.
31. Jenny-Avital ER, Abadi M. Immune reconstitution cryptococcosis after initiation of successful highly active antiretroviral therapy. Clin Infect Dis 2002; 35:e128–e133.

HIV; AIDS; ART; antiretroviral; mortality; cohort; Africa

© 2005 Lippincott Williams & Wilkins, Inc.