Access to antiretroviral therapy in HIV-infected children aged 0–19 years in the International Epidemiology Databases to Evaluate AIDS (IeDEA) Global Cohort Consortium, 2004–2015: A prospective cohort study
In a research article, Valériane Leroy and colleagues study access to antiretroviral therapy in a large population of children and adolescents with HIV-1 infection across 6 regions, and identify priorities for improving access to treatment.
In a research article, Valériane Leroy and colleagues study access to antiretroviral therapy in a large population of children and adolescents with HIV-1 infection across 6 regions, and identify priorities for improving access to treatment.
By the end of 2016, the Joint United Nations Programme on HIV/AIDS (UNAIDS) estimated that 2.1 million children aged <15 years were living with HIV worldwide . Despite effective interventions for the prevention of mother-to-child transmission, the pediatric epidemic persists, and an estimated 160,000 children were newly infected with HIV in 2016 . Furthermore, the incidence of HIV remains alarmingly high in adolescents and young people aged 15–24 years. According to UNAIDS, 37% of new HIV infections occurring in sub-Saharan African adults in 2016 were among this population .
In the absence of timely antiretroviral therapy (ART), mortality in HIV-infected children reaches 52% by the age of 2 years . Systematic early ART initiation in infants <3 months of age has proven an effective intervention in reducing early infant mortality, and the World Health Organization (WHO) has recommended ART in all HIV-infected children aged <2 years since 2010; in 2013, the recommendation to initiate ART regardless of clinical stage or CD4 count was extended to children <5 years [3–5]. In 2015, guidelines were revised to recommend ART initiation regardless of age, clinical, or immunological criteria . However, in 2015, 49% of children aged <15 years who were eligible for ART based on previous guidelines were still not receiving treatment worldwide . Many of those children who did not initiate ART either had no access to treatment or had unknown HIV status, mainly through lack of access to early HIV diagnosis.
In 2014, UNAIDS set the ambitious targets that, by 2020, 90% of people living with HIV should know their HIV status, 90% of people who know their HIV status should receive treatment, and 90% of people on treatment should be virologically suppressed . However, in low-income and middle-income countries, attrition across the continuum of care for HIV-infected children between their HIV diagnosis and ART initiation is not well known. The period between diagnosis of HIV infection and ART initiation, which includes periods from testing to linkage to care and then from inclusion in care to ART initiation, is known as the pre-ART cascade. Throughout the pre-ART period, children are at risk for attrition due to death and loss to follow-up (LTFU). A better understanding of the attrition of children across the pre-ART cascade is crucial to reach the 90-90-90 targets, particularly for the second target, to initiate ART in 90% of HIV-infected children identified, assuming that 90% have been identified among those HIV infected.
In 2006, the US National Institutes of Health launched the International Epidemiology Databases to Evaluate AIDS (IeDEA) to describe trends in HIV epidemiology in the context of ART access across regions of the world (https://www.iedea.org/). Clinics from 7 international regional data centers contribute both retrospective cohort data, prior to 2006, and prospective data since, on care and treatment of HIV to evaluate the outcomes of people living with HIV/AIDS. To better understand the continuum of care from HIV diagnosis to ART initiation in HIV-infected children and in collaboration with WHO, we performed a multiregional analysis of the pre-ART retention cascade of HIV-infected children from HIV diagnosis to ART initiation within IeDEA from 2004 to 2015.
Study design and population
This multiregional analysis was prespecified, except for the sensitivity analysis, in an approved concept plan available in the Supporting Information (S1 Concept Plan). We pooled individual patient data from 6 pediatric cohorts of IeDEA and included clinical care sites from Asia-Pacific, West Africa, East Africa, Central Africa, Southern Africa, and Latin America. We included all HIV-infected children aged 0–19 years at enrollment into any IeDEA-affiliated pediatric care program who were ART-naïve at enrollment (except for exposure to perinatal prevention of mother-to-child transmission prophylaxis) between 1 January 2004 (corresponding to the beginning of the era of ART access in low-income countries) and 31 December 2015.
Although each clinic within IeDEA has its own protocol for routine follow-up, HIV-infected children who have not yet been initiated on ART are typically seen at least every 6 months.
The data abstracted for this analysis were from routine care and included region, country, site, patient demographics (sex, date of birth, date of HIV diagnosis if available, and date of enrollment in care), clinical WHO/CDC staging at enrollment and ART initiation, laboratory values and dates (CD4 cell count, CD4 percent), cotrimoxazole start date, date of ART initiation, ART regimen, and date of death, LTFU, or transfer out.
Outcomes and key variable definitions
The outcomes of interest were (1) time to ART initiation and (2) missed opportunities for ART initiation, defined as either death or LTFU (last clinical visit >6 months before database closure and whereabouts unknown). Baseline was defined as the date of diagnosis, whether this occurred before or after enrollment in the HIV care program; when this date was unavailable, which was frequent in these contexts, we defined baseline as the date of enrollment in the HIV care program. The follow-up period was defined as the time between baseline and the date of ART initiation, death, LTFU, transfer out, or database closure (31 December 2015), whichever came first.
We assessed the proportion of children initiating ART and the proportion with missed opportunities for ART initiation (death or LTFU) within the first 24 months after enrollment. This conservative time-point was prespecified to provide a reference analysis in scaling up HIV diagnosis and ART initiation before the treat-all era from 2015 onwards. Baseline categorical data are presented as frequency (percent), and continuous data are presented as median (interquartile range [IQR]). Continuous variables were compared using the Kruskal–Wallis test, and categorical variables using the chi-squared or Fisher’s test. Time to ART initiation was estimated using cumulative incidence functions (CIFs): mortality and LTFU were considered competing events to ART initiation , while those transferred out were right-censored, with the assumption that they remained in HIV care and had similar outcomes as patients still in observation.
To better understand the different patterns of ART initiation, taking into account the evolving WHO eligibility criteria for ART initiation between 2004 and 2015 [4,5,10,11], we described the percentage of children eligible for ART initiation at baseline and during follow-up according to WHO guidelines, combining clinical criteria (WHO stage 3 or 4 or AIDS, though these data were unavailable in the Southern Africa database) and severe immunodeficiency for age (CD4 ≤ 25% if age < 5 years or CD4 ≤ 350 cells/μl if age ≥ 5 years) if enrollment in care occurred prior to 1 April 2008; additional age criteria were added if enrolled later (age <1 year between 1 April 2008 and 30 June 2010, age < 2 years between 1 July 2010 and 31 May 2013, and age < 5 years on or after 1 June 2013).
Correlates of ART initiation were described in a multivariate competing risks analysis using the Fine and Gray proportional sub-distribution hazards regression model, where time of origin was baseline . Explanatory variables included sex, age at baseline, region, country income as defined by the World Bank (http://data.worldbank.org/about/country-and-lending-groups), period of enrollment based on the changing WHO treatment guidelines (before April 2008, April 2008–June 2010, July 2010–May 2013, and after May 2013), and clinical/immunological criteria for ART eligibility at baseline and during follow-up. Model fit was checked graphically, plotting the Schoenfeld-type residuals against time for each of the covariates included in the model; we used the %pshreg SAS macro for this [13,14].
There was a high degree of variability of data collection practices across the HIV programs included in IeDEA, and some centers followed up only children who were eligible at baseline to be initiated on ART. It is likely that those programs only recorded data if children initiated ART or were intended to initiate ART before being followed up in a decentralized center. Consequently, incidence of ART initiation among all children in HIV care may be overestimated by these programs. For this reason, we performed an un-prespecified sensitivity analysis excluding the clinics where the ART coverage was >95% of all the patients followed up.
Analyses were conducted using the package cmprsk in R statistical software version 2.11.1 (R Foundation for Statistical Computing, Vienna, Austria). The adjusted sub-distribution hazard ratios (asHRs) were reported with their 95% confidence intervals (CIs). A p-value less than 0.05 was considered statistically significant.
Each participating IeDEA region formally agreed to contribute pediatric data, with local institutional review board and US National Institutes of Health approvals to contribute to multiregional analyses.
Baseline characteristics and follow-up
Overall, 180,419 children and adolescents were included in the IeDEA, of whom 120,413 were <15 years; this represents about 6% of all children living with HIV worldwide according to UNAIDS estimates. Of these, 3,262 (1.9%) were excluded due to incoherent data, 35,439 (19.6%) because they were >19 years of age, 2,194 (1.2%) because they were not ART-naïve at baseline—these children most likely entered in IeDEA active files transferring from other clinics while they were already on ART but without a date of ART initiation—and 4,045 (2.2%) because the date of enrollment in the site was before 2004 or after 2015, leaving 135,479 (75.1%) who met the inclusion criteria and were included in the study; 69.2% were from Southern Africa. Among all children included, 27,831 (20.5%) had a documented date of HIV diagnosis at or after enrollment (for those HIV-exposed) and 18,035 (13.3%) had a documented date of HIV diagnosis prior to enrollment; for the remaining 89,613 (66.1%), the date of enrollment was used as baseline (Fig 1).
Table 1 describes the patients’ characteristics at baseline. Children were enrolled at a late age, 6 years in median (IQR: 2–12), but the median age varied by region, ranging from 4 years in West Africa (IQR: 2–9) and Asia-Pacific (IQR: 2–7) to 8 years in Latin America (IQR: 2–16). This variation was mainly driven by the proportion of adolescents enrolled in the HIV care programs in each region. Overall, 32.1% of children were adolescents (≥10 years) at baseline. This varied across regions, with Asia-Pacific having the smallest proportion (9.9%), and Latin America the largest (43.2%). Children aged 5–9 years were the most commonly represented group overall (23.5%). Median CD4 percentage at baseline was 17% (IQR: 10%–25%) overall: 12% in Asia-Pacific, 15% in West Africa, 16% in Central Africa and Latin America, 17% in Southern Africa, and 19% in East Africa (p < 0.01). At the time of their enrollment, 49.1% of children were known to be eligible for ART initiation according to WHO recommendations. This percentage ranged from 43.0% in Central Africa to 74.5% in the Asia-Pacific region. Forty-eight percent of children could not be classified for ART eligibility at baseline due to missing clinical and/or immunological data.
Access to care varied greatly over regions. Overall, 31.5% of children were enrolled prior to April 2008; this represented 52.9% of the cohort in the Asia-Pacific region but only 28.1% in Southern Africa. Of all children in the database, 66.1% did not have a date of confirmed HIV diagnosis in the database: in Latin America and Asia-Pacific, a smaller proportion of children lacked HIV diagnosis date (0.0% and 2.8%, respectively), but in Southern Africa this proportion was 78.4%. Among those with a date of confirmed HIV diagnosis, 39.3% of children were diagnosed prior to enrollment in IeDEA, ranging from 14.8% in East Africa to 60.3% in West Africa (p < 0.001; Table 1); the overall median time to enrollment in care since HIV diagnosis among these children was 1 month (IQR: 0–7).
Incidence of ART initiation
Among the 135,479 children included in the study, 99,404 (73.4%) initiated ART. The median time to ART initiation was 1 month (IQR: 0–6 months); 1.9% died, 1.4% were transferred out, and 20.4% were lost to follow-up before any ART initiation (Table 2). Time to ART initiation varied according to the timing of diagnosis. Among those diagnosed prior to enrollment in care, the median time to ART since diagnosis was 4 months (IQR: 1–19); among those diagnosed after enrollment in care, median time to ART was 3 months (IQR: 1–10). Among those with no documented date of HIV diagnosis, median time from enrollment to ART was 1 month (IQR: 0–5). Finally, among those enrolled at time of diagnosis, the median time from baseline to ART was 2 months (IQR: 0–8).
After 1 month of pre-ART follow-up, the CIF for ART initiation in all HIV-infected children was estimated to be 35.7% (95% CI: 35.4%–35.9%) while the CIF for missed opportunities (death or LTFU) was 10.7% (95% CI: 10.5%–10.9%). By 24 months of pre-ART follow-up, the CIF for ART initiation had reached 68.2% (95% CI: 67.9%–68.4%), and the 24-month cumulative incidence for missed opportunities was 19.3% (95% CI: 19.1%–19.5%). Fig 2A presents the 24-month CIF for time to ART initiation since baseline by region. It was 71.0% (95% CI: 69.1%–72.7%) and 78.3% (95% CI: 76.9%–79.6%) for Latin America and the Asia-Pacific, respectively. In sub-Saharan Africa, the 24-month CIF for ART initiation was significantly lower, ranging from 49.8% (95% CI: 48.4%–51.2%) in Central Africa to 60.9% (95% CI: 60.3%–61.6%) in East Africa, 70.1% (95% CI: 69.8%–70.4%) in Southern Africa, and 72.5% (95% CI: 71.5%–73.5%) in West Africa. We also noted that results differed by age at baseline: children and adolescents aged 15–19 years and those aged <1 year at baseline had the lowest ART initiation rates compared to other ages, with a 24-month CIF of 62.2% (95% CI: 61.6%–62.8%) and 66.4% (95% CI: 65.7%–67.0%), respectively (Fig 2B).
Fig 2C presents CIFs for ART initiation according to ART eligibility at baseline. Among children eligible at baseline, the 24-month CIF was 78.6% (95% CI: 78.3%–78.9%) compared to 56.4% (95% CI: 55.1%–57.7%) among those known not to be eligible at baseline who became eligible during follow-up. We also note that the CIF for ART initiation reached 39.4% (95% CI: 37.6%–41.1%) at 24 months among children who did not meet ART eligibility criteria. Among those with unknown eligibility criteria at baseline, the 24-month CIF for ART initiation was 58.7% (95% CI: 58.3%–59.1%) (S3 Fig).
ART initiation according to ART eligibility
To better understand the patterns of ART initiation, we present the ART eligibility for the overall population (Fig 3). Of the 135,479 children included in the analysis, 66,482 (49.1%) were known to be eligible for ART initiation according to WHO criteria at baseline, of whom 53,616 (80.6%) initiated ART. Among the 3,674 (2.7%) not eligible for ART at baseline, 5 (0.1%) became eligible during follow-up, of whom all initiated ART. Among the 65,323 (48.2%) who were not classified for ART eligibility at baseline due to missing clinical and/or immunological data, 5,345 (8.2%) became eligible, of whom 4,275 (80.0%) initiated ART, and 692 (1%) did not meet eligibility criteria during follow-up, of whom 398 (57%) initiated ART. Overall, 13,936 (19.4%) children known to be eligible for ART initiation, either at baseline or during follow-up, never accessed treatment over the first 24 months of follow-up. These missed opportunities for ART initiation highlight a substantial proportion of unmet needs.
In 2015, no region had yet reached the UNAIDS target of 90% of those diagnosed with HIV infection on ART, though the Asia-Pacific, Latin America, and Southern and West Africa IeDEA regions had percentages of ART initiation close to 80% (Fig 4). Central and East Africa had the lowest coverage (49% and 59%, respectively). A substantial proportion of eligible children did not initiate ART during the study period, ranging from 9% in Latin America to 15% in West Africa and 16% in Central Africa.
Correlates of ART initiation
In the multivariate Fine and Gray analysis, sex, region, age at baseline, period of enrollment, country income, and clinical or immunological eligibility were all associated with ART initiation (Table 3). Adjusted for the above variables, females were less likely to initiate ART compared to their male counterparts (asHR: 0.94, 95% CI: 0.92–0.95). Compared to Latin America, 3 sub-Saharan African regions were less likely to initiate ART, with asHRs ranging from 0.69 (95% CI: 0.66–0.72) in Central Africa and 0.80 (95% CI: 0.77–0.83) in East Africa to 0.93 (95% CI: 0.90–0.97) in Southern Africa. Children from the Asia-Pacific and West Africa regions had similar hazard of treatment initiation compared to those from Latin America (asHR: 1.01, 95% CI: 0.97–1.05, and asHR: 1.02, 95% CI: 0.97–1.06, respectively). Adolescents aged 10–14 years at baseline were the most likely to initiate ART compared to all other age groups. Infants aged <1 year and adolescents aged ≥15 years were less likely to initiate ART compared to those 10–14 years old (asHR: 0.83, 95% CI: 0.81–0.85, and asHR: 0.73, 95% CI: 0.71–0.75, respectively). Children enrolled prior to June 2013 were also less likely to initiate ART than those enrolled more recently, adjusted for other variables, and we noted a tendency towards lower likelihood of initiating ART in earlier enrollment periods (asHR: 0.78, 95% CI: 0.76–0.80, for those with enrollment in July 2010–May 2013; asHR: 0.63,95% CI: 0.61–0.64, for those enrolled in the period April 2008–June 2010; and asHR: 0.57, 95% CI: 0.55–0.58, for those enrolled prior to April 2008) compared to those enrolled in or beyond June 2013. ART initiation was also associated with country income: children from countries of low or lower middle income were less likely to initiate ART compared to those from upper-middle- and high-income settings (asHR: 0.76, 95% CI: 0.75–0.78). Finally, we found that children who became eligible for ART initiation (per clinical and/or immunological criteria, but not on age criteria—that was a separate variable) during follow-up were less likely to initiate ART compared to those who were eligible at baseline (asHR: 0.61, 95% CI: 0.60–0.63).
Overall, 112,134 children were followed up in clinics where ART coverage was ≤95%. Results are presented in the Supporting Information (S2 and S3 Figs; S1 Table). Among these children, the 24-month CIF for ART initiation was estimated to be much lower than in the whole population, at 62.9% (95% CI: 62.6%–63.2%), and the 24-month probability for missed opportunities for ART was higher, at 23.3% (95% CI: 23.1%–23.6%), than in the whole population (S2 Fig). The children from Asia-Pacific had the highest ART initiation rates, reaching 73.1% (95% CI: 71.4%–74.8%), compared to all others, including those from sub-Saharan Africa, with 49.8% (95% CI: 48.4%–51.2%) in Central Africa, 60.2% (95% CI: 58.8%–61.7%) in West Africa, 60.9% (95% CI: 58.8%–61.7%) in East Africa, and 60.2% (95% CI: 58.8%–61.7%) in Southern Africa (S3 Fig). In the multivariate Fine and Gray competing risk analysis, we did not observe significant changes in correlates of ART initiation in this population, except for the effect of region, with the lowest asHR for ART initiation in sub-Saharan Africa compared to Latin America, ranging from 0.60 in Central Africa (95% CI: 0.57–0.63) and West Africa (95% CI: 0.57–0.63) and 0.70 in East Africa (95% CI: 0.67–0.73) to 0.80 in Southern Africa (95% CI: 0.77–0.83) (S1 Table).
This pooled analysis from the IeDEA Global Cohort Consortium documents time to ART initiation since enrollment in HIV programs treating HIV-infected children and adolescents between the ages of 0 and 19 years within multiple geographic regions, between 2004 and 2015. We report 3 major findings. First, in HIV-infected children and adolescents, the cumulative incidence of initiating ART within 24 months of enrollment into a program or HIV diagnosis was 68%, with a substantial risk for mortality or LTFU before ART initiation (19%), representing multiple missed opportunities for ART initiation. Second, among children eligible for ART initiation and followed up, 19% did not initiate treatment within the first 24 months of follow-up. Third, we report a number of inequities in ART access: female sex, children <10 years at baseline (and those <1 year in particular), adolescents aged 15–19 years at baseline (compared to those aged 10–14 years), those becoming eligible during follow-up (compared to those eligible at baseline), and those living in sub-Saharan Africa compared to other regions were all less likely to initiate treatment.
The 24-month cumulative incidence for ART initiation was 68%. According to ART eligibility, this was 78.6% among those eligible at baseline and 56.4% among those who became eligible during the study. While these rates are low compared to the UNAIDS target of 90% of those diagnosed with HIV, they are encouraging compared to previous available studies. For example, in South Africa, only 34.8% of ART-eligible HIV-infected children initiated ART in 2003 . More recently, in Lesotho, 41.2% of eligible children initiated ART in 2008 . In Côte d’Ivoire, 55% of eligible children initiated ART in 2009 . Still, the rate of ART initiation among children often lags compared to adults and occurs late, despite progressive guidelines stressing immediate treatment initiation for the youngest children regardless of immunological/clinical status since 2008 .
At inclusion in HIV programs, 66.1% of children did not have a date of confirmed HIV diagnosis, median age was 6 years, and 49.1% were already eligible for ART, highlighting the late access to ART. Delayed ART initiation is most likely the result of late access to HIV diagnosis for HIV-exposed children [19,20]. Difficulties in identifying HIV-exposed infants, limited capacity to perform routine virological testing in HIV-exposed infants, and long result turnaround time remain important barriers to timely initiation of treatment . In addition, the lack of integration of prevention of mother-to-child transmission and pediatric HIV care programs hampers the delivery of early infant diagnosis . This is mainly related to infrastructure limitations and time constraints as well as staff shortages [20,22,23]. In older children, similar structural barriers have been identified , along with additional key barriers such as stigma, lack of knowledge in the adolescent population, and socio-cultural beliefs [24–27].
There are many points at which children may drop out the HIV care cascade. First and foremost, linkage to care after HIV diagnosis remains a complex issue . There are many reasons for failing to link a child to care including fear of stigma [29–31], community and economic factors such as lack of support and finances for transport, missed days of work, and healthcare worker and infrastructure constraints (e.g., drug stock outs, lack of knowledge among providers on when to prescribe ART, patients missing appointments, eligible patients not identified appropriately) [32,33]. Challenges continue even after linkage to care. Although our results demonstrate the feasibility of large-scale ART rollout for children, 1.9% died and 20.4% were lost to follow-up before ART initiation. Some of the children who were lost to HIV care programs may represent undocumented mortality, but they may also be out of care or may have transferred to other facilities without documentation. Once children were linked to HIV care, we also observed suboptimal rates of ART initiation among children who became eligible during follow-up compared to those eligible at enrollment, further undermining the HIV care cascade.
Direct comparisons with other studies are made difficult by differences in methodology and definition of outcomes, but our observations underline the many missed opportunities for ART initiation and the difficulties in keeping children in the pre-ART care cascade. Low retention among HIV-diagnosed patients waiting to initiate ART, as observed in our study, has also been previously described in both adult and pediatric populations. Most losses happen between HIV diagnosis and CD4 staging . Current guidelines no longer require CD4 staging to start ART, which may contribute to improved retention in care and access to ART.
Weaknesses in the continuity of care services must urgently be addressed in order to improve ART coverage and survival among HIV-infected children. For perinatally infected children, other interventions such as family-centered models have also been proposed to improve linkage to care after diagnosis [35,36]. In older children, use of youth-friendly models of care may be an important intervention [37–39]. Regardless of the mode and age at infection, multiple efforts are necessary to reach high uptake of services [40,41]. HIV testing and care need to be decentralized and brought to communities . There is a need to support families and healthcare workers to provide HIV services for children [6,43,44]. Finally, the “test and treat” strategy recommended by WHO in 2015 that advocates starting HIV-infected individuals on ART immediately regardless of any eligibility criteria could further prevent these missed opportunities for ART initiation among HIV-diagnosed children.
We observed disparities in ART initiation between regions, with 24-month cumulative incidence of ART initiation ranging from <75% in sub-Saharan Africa to 78.3% in Asia-Pacific. This variability could be partly explained by the smaller number of HIV-infected children treated in Asia-Pacific compared to sub-Saharan Africa, with a larger sample size .
We also highlight other inequities in the rollout of ART. Females, children aged <10 years, and in particular those aged <1 year, along with adolescents aged ≥15 years, were less likely to initiate treatment. Previous studies have reported on missed opportunities for ART initiation in both very young children, mostly explained by early mortality before accessing HIV diagnosis and subsequent ART initiation, and adolescents, where fear of stigma in the family and community as well as parental consent requirements are major barriers [25,40,45]. Missed opportunities for ART initiation in adolescents aged 15–19 years could also be a reflection of noncompliance with visits. In addition, we observed that children who became eligible during follow-up were less likely to initiate treatment (asHR: 0.69, 95% CI: 0.68–0.70) compared to those eligible at enrollment. From a programmatic point of view, this observation strongly supports the universal “test and treat” strategy .
Our results indicate insufficient levels of ART initiation among children who were treatment eligible over the whole study period, but we also observed a gradual improvement in these rates during more recent time periods. As WHO guidelines began recommending universal ART in all children and adolescents irrespective of clinical stage or CD4 count in 2015, we expect the number needed to be treated increased in 2016. While there are still many obstacles that will impede the target of 90% ART coverage, there is an ethical priority to trace all HIV-exposed children in order to determine HIV status and link them into care if HIV infected and to treat all children who have already linked to care.
This study has major strengths but also several limitations. First, time to ART initiation since HIV diagnosis may be incorrectly estimated as data regarding confirmed dates of HIV diagnosis were scarce. We used enrollment as a proxy for HIV diagnosis, and therefore time between HIV diagnosis and ART initiation is likely underestimated in programs that do not have well-documented HIV diagnosis dates. Furthermore, a left-truncation phenomenon would mask deaths among HIV-infected children between their HIV diagnosis and inclusion into HIV programs. This survivor bias undoubtedly leads to further underestimation of the incidence of missed opportunities for ART initiation among HIV-infected children, and, consequently, the true cumulative incidence of ART initiation among all HIV-infected children is likely lower than that estimated by these data. Our results illustrate this well: programs where higher proportions were eligible at diagnosis seemed to do better in terms of ART initiation, whereas in reality these programs were doing worse as many children were diagnosed too late, with advanced HIV disease at entry. Imputation of time of diagnosis for those with missing date of diagnosis could have addressed this limitation in theory, but missing values were too numerous for this to be done. Because diagnosis is often performed at the same time as inclusion in care, our results reflect as best as possible the situation in routine care.
Second, we observed limitations inherent to data quality: 45% of children had missing data on variables used to assess ART eligibility. We thus advise caution in the interpretation of our results, particularly in the context of current universal treatment recommendations. Third, 24-month incidence of ART initiation and missed opportunities for care were derived from data collected over a 10-year period, during which both national and international guidelines varied over time. Although we adjusted for evolving ART eligibility criteria during follow-up in our final model to address this, further analyses would be necessary to better describe the progress made and treatment gaps on a national level.
Fourth, the outcomes of children lost to follow-up were not well known, and the high proportion of children lost to follow-up (20.4%) includes undocumented mortality, those out of care, and silent transfers. Both death and being out of care represent poor outcomes from missed opportunities, but silent transfers may or may not represent ultimate ART initiation. In the absence of outreach data, it is unclear how these results should be interpreted. To overcome these limitations, we combined mortality and LTFU as a single outcome (of programmatic failure) in estimating the cumulative rate of missed opportunities for ART initiation after enrollment in an HIV care program.
Fifth, HIV programs across and within regions vary. Some programs were specific to children once they started therapy, making it likely that those programs only recorded data if children initiated ART or were intended to initiate ART but not during the pre-ART period. As a result, our analysis may further overestimate the overall proportion of HIV-infected children starting ART as the denominator of all children may have shrunk in these instances. In sensitivity analyses where we excluded such programs from consideration, we observed no significant differences in our results, except in overall and regional ART initiation probabilities, which, as expected, were lower when restricted to sites with ART coverage ≤95%.
The mitigating factor of all these limitations is that the bias in estimating overall cumulative ART initiation rates goes in one direction, leading to overestimation of the cumulative rate of the start of treatment. This actually strengthens rather than undermines our conclusions regarding the continued challenge of universal care and treatment of children and adolescents living with HIV around the world. In addition, our study is the largest study reported to our knowledge to document the global pre-ART cascade in pediatrics in 2015, including data from a large number of diverse programs with significant geographic coverage; this study is a generalizable, authoritative investigation of the state of the worldwide response to the HIV epidemic in pediatric and adolescent populations living with HIV.
In conclusion, this large global cohort study of children with HIV reported a 24-month cumulative incidence of ART initiation of 68.2% between 2004 and 2015, and a high 19.3% cumulative incidence of program attrition prior to treatment start driven by mortality and loss to programs. Given the limitations to our study data, actual coverage of ART initiation in children during the study period is likely to have been lower than the estimates reported. As of 2015, there remain many obstacles to ART initiation, with substantial risks of loss to programs and death before ART initiation in the context of incomplete early infant diagnosis, linkage to care, and treatment initiation even after enrollment in care. In particular, infants <1 year of age and older adolescents urgently need more effective and targeted interventions to improve their HIV testing uptake and access to ART in order to facilitate their survival. With expanding adoption of universal treatment recommendations since 2015, it will be crucial to further monitor progress and identify gaps in ART coverage to achieve the 90-90-90 targets for children and adolescents.
1. Joint United Nations Programme on HIV/AIDS. UNAIDS data 2017. Geneva: Joint United Nations Programme on HIV/AIDS; 2017 [cited 2018 Mar 16]. Available from: http://www.unaids.org/sites/default/files/media_asset/2017_data-book_en.pdf.
2. Newell ML, Coovadia H, Cortina Borja M, Rollins N, Gaillard P, Dabis F,et al. Mortality of infected and uninfected infants born to HIV-infected mothers in Africa: a pooled analysis. Lancet. 2004;364:1236–43. doi: 10.1016/S0140-6736(04)17140-7 15464184
3. Violari A, Cotton MF, Gibb DM, Babiker AG, Steyn J, Madhi SA, et al. Early antiretroviral therapy and mortality among HIV-infected infants. N Engl J Med. 2008;359:2233–44. doi: 10.1056/NEJMoa0800971 19020325
4. World Health Organization. Consolidated guidelines on the use of antiretroviral drugs for treating and preventing HIV infection: recommendations for a public health approach. Geneva: World Health Organization; 2013 [cited 2018 Mar 16]. Available from: http://www.who.int/hiv/pub/guidelines/arv2013/en/index.html.
5. World Health Organization, Joint United Nations Programme on HIV/AIDS, United Nations Children’s Fund. Towards universal access: scaling up priority HIV/AIDS interventions in the health sector. Progress report 2010. Geneva: World Health Organization; 2010 [cited 2018 Mar 16]. Available from: http://whqlibdoc.who.int/publications/2010/9789241500395_eng.pdf.
6. World Health Organization. Consolidated guidelines on the use of antiretroviral drugs for treating and preventing HIV infection: recommendations for a public health approach—second edition. Geneva: World Health Organization; 2016 [cited 2018 Mar 16]. Available from: http://www.who.int/hiv/pub/arv/arv-2016/en/.
7. Joint United Nations Programme on HIV/AIDS. On the fast track to an AIDS-free generation. Geneva: Joint United Nations Programme on HIV/AIDS; 2015 [cited 2018 Mar 16]. Available from: http://www.unaids.org/sites/default/files/media_asset/GlobalPlan2016_en.pdf.
8. Joint United Nations Programme on HIV/AIDS. The 90-90-90: an ambitious treatment target to help end the AIDS epidemic. Geneva: Joint United Nations Programme on HIV/AIDS; 2014 [cited 2018 Apr 6]. Available from: http://www.unaids.org/sites/default/files/media_asset/90-90-90_en.pdf.
9. Chamla D, Mbori-Ngacha D, Newman M, Kellerman SE, Sugandhi N, Rwebembera A, et al. Evidence from the field: missed opportunities for identifying and linking HIV-infected children for early initiation of ART. AIDS. 2013;27(Suppl 2):S139–46.
10. World Health Organization. Antiretroviral therapy of HIV infection in infants and children in resource-limited settings: towards universal access. Recommendations for a public health approach. Geneva: World Health Organization; 2006 [cited 2018Apr 6]. Available from: http://www.who.int/hiv/pub/guidelines/WHOpaediatric.pdf.
11. World Health Organization. Guideline on when to start antiretroviral therapy and on pre-exposure prophylaxis for HIV. Geneva: World Health Organization; 2015 [cited 2018 Mar 16]. Available from: http://apps.who.int/iris/bitstream/10665/186275/1/9789241509565_eng.pdf?ua=1.
12. Scrucca L, Santucci A, Aversa F. Regression modeling of competing risk using R: an in depth guide for clinicians. Bone Marrow Transplant. 2010;45:1388–95. doi: 10.1038/bmt.2009.359 20062101
13. Li J, Scheike TH, Zhang MJ. Checking Fine and Gray subdistribution hazards model with cumulative sums of residuals. Lifetime Data Anal. 2015;21:197–217. doi: 10.1007/s10985-014-9313-9 25421251
14. Kohl M, Plischke M, Leffondre K, Heinze G. PSHREG: a SAS macro for proportional and nonproportional subdistribution hazards regression. Comput Methods Programs Biomed. 2015;118:218–33. doi: 10.1016/j.cmpb.2014.11.009 25572709
15. Feucht UD, Kinzer M, Kruger M. Reasons for delay in initiation of antiretroviral therapy in a population of HIV-infected South African children. J Trop Pediatr. 2007;53:398–402. doi: 10.1093/tropej/fmm060 17965099
16. Leyenaar JK, Novosad PM, Ferrer KT, Thahane LK, Mohapi EQ, Schutze GE, et al. Early clinical outcomes in children enrolled in human immunodeficiency virus infection care and treatment in Lesotho. Pediatr Infect Dis J. 2010;29:340–5. doi: 10.1097/INF.0b013e3181bf8ecb 20019645
17. Anaky MF, Duvignac J, Wemin L, Kouakoussui A, Karcher S, Touré S, et al. Scaling up antiretroviral therapy for HIV-infected children in Cote d’Ivoire: determinants of survival and loss to programme. Bull World Health Organ. 2010;88:490–9. doi: 10.2471/BLT.09.068015 20616968
18. Leroy V, Malateste K, Rabie H, Lumbiganon P, Ayaya S, Dicko F, et al. Outcomes of antiretroviral therapy in children in Asia and Africa: a comparative analysis of the IeDEA pediatric multiregional collaboration. J Acquir Immune Defic Syndr. 2013;62:208–19. doi: 10.1097/QAI.0b013e31827b70bf 23187940
19. Penazzato M, Revill P, Prendergast AJ, Collins IJ, Walker S, Elyanu PJ, et al. Early infant diagnosis of HIV infection in low-income and middle-income countries: does one size fit all? Lancet Infect Dis. 2014;14:650–5. doi: 10.1016/S1473-3099(13)70262-7 24456814
20. Ciaranello AL, Park J, Ramirez-Avila L, Freedberg KA, Walensky RP, Leroy V. Early infant HIV-1 diagnosis programs in resource-limited settings: opportunities for improved outcomes and more cost-effective interventions. BMC Med. 2011;9:59. doi: 10.1186/1741-7015-9-59 21599888
21. Edmonds A, Feinstein L, Okitolonda V, Thompson D, Kawende B, Behets F. Implementation and operational research: decentralization does not assure optimal delivery of PMTCT and HIV-exposed infant services in a low prevalence setting. J Acquir Immune Defic Syndr. 2015;70:e130–9. doi: 10.1097/QAI.0000000000000781 26262776
22. Hassan AS, Sakwa EM, Nabwera HM, Taegtmeyer MM, Kimutai RM, Sanders EJ, et al. Dynamics and constraints of early infant diagnosis of HIV infection in rural Kenya. AIDS Behav. 2012;16:5–12. doi: 10.1007/s10461-010-9877-7 21213034
23. Geelhoed D, Lafort Y, Chissale E, Candrinho B, Degomme O. Integrated maternal and child health services in Mozambique: structural health system limitations overshadow its effect on follow-up of HIV-exposed infants. BMC Health Serv Res. 2013;13:207. doi: 10.1186/1472-6963-13-207 23758816
24. Coulibaly M, Meda N, Yonaba C, Ouedraogo S, Congo M, Barry M, et al. Missed opportunities for early access to care of HIV-infected infants in Burkina Faso. PLoS ONE. 2014;9:e111240. doi: 10.1371/journal.pone.0111240 25360551
25. Dahourou DL, Amorissani-Folquet M, Coulibaly M, Avit-Edi D, Meda N, Timite-Konan M, et al. Missed opportunities of inclusion in a cohort of HIV-infected children to initiate antiretroviral treatment before the age of two in West Africa, 2011 to 2013. J Int AIDS Soc. 2016;19:20601. doi: 10.7448/IAS.19.1.20601 27015798
26. De Schacht C, Lucas C, Mboa C, Gill M, Macasse E, Dimande SA, et al. Access to HIV prevention and care for HIV-exposed and HIV-infected children: a qualitative study in rural and urban Mozambique. BMC Public Health. 2014;14:1240. doi: 10.1186/1471-2458-14-1240 25467030
27. Ndondoki C, Brou H, Timite Konan M, Oga M, Amani Bosse C, Menan H, et al. Universal HIV screening at postnatal points of care: which public health approach for early infant diagnosis in Côte d’Ivoire? PLoS ONE. 2013;8:e67996. doi: 10.1371/journal.pone.0067996 23990870
28. Phelps BR, Ahmed S, Amzel A, Diallo MO, Jacobs T, Kellerman SE, et al. Linkage, initiation and retention of children in the antiretroviral therapy cascade: an overview. AIDS. 2013;27(Suppl 2):S207–13.
29. Russell S, Zalwango F, Namukwaya S, Katongole J, Muhumuza R, Nalugya R, et al. Antiretroviral therapy and changing patterns of HIV stigmatisation in Entebbe, Uganda. Sociol Health Illn. 2016;38:58–72. doi: 10.1111/1467-9566.12341 26382288
30. Adeniyi VO, Thomson E, Ter Goon D, Ajayi IA. Disclosure, stigma of HIV positive child and access to early infant diagnosis in the rural communities of OR Tambo District, South Africa: a qualitative exploration of maternal perspective. BMC Pediatr. 2015;15:98. doi: 10.1186/s12887-015-0414-8 26306387
31. Neuman M, Obermeyer CM. Experiences of stigma, discrimination, care and support among people living with HIV: a four country study. AIDS Behav. 2013;17:1796–808. doi: 10.1007/s10461-013-0432-1 23479002
32. Maman S, Cathcart R, Burkhardt G, Omba S, Behets F. The role of religion in HIV-positive women’s disclosure experiences and coping strategies in Kinshasa, Democratic Republic of Congo. Soc Sci Med. 2009;68:965–70. doi: 10.1016/j.socscimed.2008.12.028 19136188
33. Manzi M, Zachariah R, Teck R, Buhendwa L, Kazima J, Bakali E, et al. High acceptability of voluntary counselling and HIV-testing but unacceptable loss to follow up in a prevention of mother-to-child HIV transmission programme in rural Malawi: scaling-up requires a different way of acting. Trop Med Int Health. 2005;10:1242–50. doi: 10.1111/j.1365-3156.2005.01526.x 16359404
34. Rosen S, Fox MP. Retention in HIV care between testing and treatment in sub-Saharan Africa: a systematic review. PLoS Med. 2011;8:e1001056. doi: 10.1371/journal.pmed.1001056 21811403
35. Thomson KA, Cheti EO, Reid T. Implementation and outcomes of an active defaulter tracing system for HIV, prevention of mother to child transmission of HIV (PMTCT), and TB patients in Kibera, Nairobi, Kenya. Trans R Soc Trop Med Hyg. 2011;105:320–6. doi: 10.1016/j.trstmh.2011.02.011 21511317
36. Leeper SC, Montague BT, Friedman JF, Flanigan TP. Lessons learned from family-centred models of treatment for children living with HIV: current approaches and future directions. J Int AIDS Soc. 2010;13(Suppl 2):S3.
37. Henwood R, Patten G, Barnett W, Hwang B, Metcalf C, Hacking D, et al. Acceptability and use of a virtual support group for HIV-positive youth in Khayelitsha, Cape Town using the MXit social networking platform. AIDS Care. 2016;28:898–903. doi: 10.1080/09540121.2016.1173638 27098208
38. Goga AE, Singh Y, Singh M, Noveve N, Magasana V, Ramraj T, et al. Enhancing HIV treatment access and outcomes amongst HIV infected children and adolescents in resource limited settings. Matern Child Health J. 2017;21:1–8.
39. Teasdale CA, Alwar T, Chege D, Fayorsey R, Hawken MP, Abrams EJ. Impact of youth and adolescent friendly services on retention of 10–24-year-olds in HIV care and treatment programs in Nyanza, Kenya. J Acquir Immune Defic Syndr. 2016;71:e56–9.
40. Boender TS, Sigaloff KC, Kayiwa J, Musiime V, Calis JC, Hamers RL, et al. Barriers to initiation of pediatric HIV treatment in Uganda: a mixed-method study. AIDS Res Treat. 2012;2012:817506. doi: 10.1155/2012/817506 22400106
41. van Dijk JH, Sutcliffe CG, Munsanje B, Hamangaba F, Thuma PE, Moss WJ. Barriers to the care of HIV-infected children in rural Zambia: a cross-sectional analysis. BMC Infect Dis. 2009;9:169. doi: 10.1186/1471-2334-9-169 19835604
42. Sweat M, Morin S, Celentano D, Mulawa M, Singh B, Mbwambo J, et al. Community-based intervention to increase HIV testing and case detection in people aged 16–32 years in Tanzania, Zimbabwe, and Thailand (NIMH Project Accept, HPTN 043): a randomised study. Lancet Infect Dis. 2011;11:525–32. doi: 10.1016/S1473-3099(11)70060-3 21546309
43. Schlatter AF, Deathe AR, Vreeman RC. The need for pediatric formulations to treat children with HIV. AIDS Res Treat. 2016;2016:1654938. doi: 10.1155/2016/1654938 27413548
44. Penazzato M, Lee J, Capparelli E, Essajee S, Ford N, Ojoo A, et al. Optimizing drugs to reach treatment targets for children and adolescents living with HIV. J Int AIDS Soc. 2015;18:20270. doi: 10.7448/IAS.18.7.20270 26639117
45. Sam-Agudu NA, Folayan MO, Ezeanolue EE. Seeking wider access to HIV testing for adolescents in sub-Saharan Africa. Pediatr Res. 2016;79:838–45. doi: 10.1038/pr.2016.28 26882367