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. Author manuscript; available in PMC: 2016 Jan 1.
Published in final edited form as: J Acquir Immune Defic Syndr. 2015 Jan 1;68(1):62–72. doi: 10.1097/QAI.0000000000000380

Immunodeficiency in children starting antiretroviral therapy in low-, middle- and high-income countries

Manuel Koller 1, Kunjal Patel 2, Benjamin H Chi 3, Kara Wools-Kaloustian 4, Fatoumata Dicko 5, Kulkanya Chokephaibulkit 6, Cleophas Chimbetete 7, Dorita Avila 1, Rohan Hazra 8, Samual Ayaya 9, Valeriane Leroy 10, Huu Khanh Trong 11, Matthias Egger 1,12, Mary-Ann Davies 12; for the IeDEA, NISDI, PHACS and IMPAACT 219C studies
PMCID: PMC4351302  NIHMSID: NIHMS631198  PMID: 25501345

Abstract

Background

The CD4 cell count or percent (CD4%) at the start of combination antiretroviral therapy (cART) are important prognostic factors in children starting therapy and an important indicator of program performance. We describe trends and determinants of CD4 measures at cART initiation in children from low-, middle- and high-income countries.

Methods

We included children aged <16 years from clinics participating in a collaborative study spanning sub-Saharan Africa, Asia, Latin America and the United States of America (USA). Missing CD4 values at cART start were estimated through multiple imputation. Severe immunodeficiency was defined according to World Health Organization criteria. Analyses used generalized additive mixed models adjusted for age, country and calendar year.

Results

34,706 children from nine low-income, six lower middle-income, four upper middle-income countries and one high-income country (United States of America, USA) were included; 20,624 children (59%) had severe immunodeficiency. In low-income countries the estimated prevalence of children starting cART with severe immunodeficiency declined from 76% in 2004 to 63% in 2010. Corresponding figures for lower middle-income countries were from 77% to 66% and for upper middle-income countries from 75% to 58%. In the USA, the percentage decreased from 42% to 19% during the period 1996 to 2006. In low- and middle-income countries infants and children aged 12-15 years had the highest prevalence of severe immunodeficiency at cART initiation.

Conclusions

Despite progress in most low- and middle-income countries, many children continue to start cART with severe immunodeficiency. Early diagnosis and treatment of HIV-infected children to prevent morbidity and mortality associated with immunodeficiency must remain a global public health priority.

Introduction

Access to combination antiretroviral therapy (cART) has increased dramatically since2004, with substantial funding from donors and national governments. According to World Health Organization (WHO) estimates, the number of children receiving cART in low- and middle-income countries increased from 71,500 at the end of 2005 to 740,000 in 2013, an increase in coverage among all HIV-infected children from 11% to 23%.1,2 However, in many settings mortality remains high during the first year of cART, especially among children with advanced disease.3-6

Immunologic status (CD4 cell count or percentage), age, and clinical stage at cART initiation are important prognostic factors for HIV-infected children and WHO guidelines for starting therapy have been based on these criteria.7 A recent prognostic model from Southern Africa estimated that mortality in the first year of treatment in children starting cART with CD4% ≥10% was about half that of children with CD4% <5%.8 Similarly, mortality in children with WHO clinical stage 3/4 was about 40% higher compared to children in stages 1/2, and about four times higher in infants compared to children 5-10 years.8

Until recently WHO guidelines recommended immediate cART regardless of immunologic or clinical thresholds for infants and children aged <2 years and for all children aged 2-5 years with WHO clinical stages 3/4, or CD4 <750 cells/μl or 25%.7 These guidelines were revised in 2013, to recommend immediate treatment for all children <5 years old.9 Previous studies indicate that most children in lower income settings do not initiate cART until they have severe immunosuppression. Among 10,875 children who initiated treatment from 2004-2010 in Malawi, South Africa, Zambia and Zimbabwe, most had advanced disease (72% WHO stage 3/4) with low median CD4% (13%).8 Temporal trends in CD4 measures at cART initiation are a useful indicator of the ability of health care systems to identify and treat eligible children in a timely fashion and to respond to changing guidelines. We analyzed these indicators from an international collaboration of treatment programs in sub-Saharan Africa, Asia, Latin America, and North America.

Methods

Data sources

The International epidemiologic Databases to Evaluate AIDS (IeDEA) is a global consortium structured through regional centers to pool data on HIV-infected individuals. The seven regions included in IeDEA are North America, Caribbean/Central and South America, Asia/Pacific, and four regions in sub-Saharan Africa (East Africa, West Africa, Central Africa and Southern Africa).6,10-14 For the present analysis we included data from the African and Asia/Pacific regions of IeDEA. In addition, we included North American and Latin American data from the NICHD International Site Development Initiative (NISDI),15 the Pediatric HIV/AIDS Cohort Study (PHACS),16 and the International Maternal Pediatric Adolescent AIDS Clinical Trials (IMPAACT) 219C study.17 Pooling of data and their use in collaborative analyses were approved by local ethics committees and institutional review boards. Participating regional centers sent de-identified data to the University of Bern, Switzerland where the data were collated and analyzed.

Inclusion criteria and definitions

All patients aged <16 years with documented gender and cART start date were included in descriptive analyses of age, gender and calendar year at cART initiation. For further analyses we excluded data from low or middle-income countries before widespread rollout began in 2003, data from calendar years from any country with <10 children with CD4 measures for that year and countries contributing <50 children with CD4 measures overall after applying the calendar year exclusion criterion. cART was defined as a regimen of ≥3 antiretroviral drugs, typically from two drug classes. Baseline CD4 values were defined as those nearest to cART start date, within a window of 6 months before to 1 month after treatment initiation. Countries were grouped according to the World Bank classification of Gross National Income per capita per year in 2010 as low-income (LIC) (≤US$1,005); lower middle-income (LMIC) (US$1,006 to 3,975); upper middle-income (UMIC) (US$3,976 to 12,275) and high-income (HIC) (≥US$12,276).18 Age groups were <12 months, 12-35 months, 36-59 months, 5-11 years and 12-15 years. Severe immunodeficiency was defined according to WHO criteria as CD4% <25% (age <12 months), <20% (age 12-35 months), <15% (age 36-59 months) and CD4 count <200 cells/μl or CD4% <15% (age ≥5 years).19

Descriptive analyses

Descriptive analyses included all countries and calendar years with any data from 1995 onwards. Analyses were stratified by country, age group, gender and country income group. CD4 values, age and calendar year at cART start were summarized as medians with interquartile ranges (IQR) or percentages.

Multiple imputation of missing CD4 measures

We imputed missing CD4 measures for countries contributing ≥50 children with CD4 measures and calendar years with ≥10 children with CD4 measures. We imputed log of CD4% and count simultaneously using chained equations and predictive mean matching, adjusting for country, year of cART start, continent and national cART coverage and stratifying by gender, age and income group. Data on pediatric cART coverage for 2009 were obtained from WHO for low- and middle-income countries.20 We generated 50 imputed datasets and combined these using Rubin's rule.21

Analyses of temporal trends in CD4 measures

We used generalized additive mixed models to analyze temporal trends in CD4 measures in different age and country income groups. We analyzed the proportion of children with severe immunodeficiency, median CD4% (aged <5 years) and median CD4 count (aged ≥5 years). Gender, age group and income group as well as their interactions were entered as fixed effects. Yearly trends were smoothed by gender, age group and income group. The data were aggregated by calendar year (3-12 years, depending on country), country (20 countries), gender (2 groups) and age group (5 groups, as defined above) prior to analysis: each combination of these factors corresponded to a cell in the analysis. For each cell we calculated the number of children with severe immunodeficiency and the median CD4% and count. Each cell was entered in the model with a weight corresponding to the number of observations it contained divided by the average number of observations in all cells. We modeled the prevalence of severe immunodeficiency using the binomial distribution and a logit link, assuming Gaussian distributions for the error terms of CD4% and count. We used the same modeling technique to model temporal trends in age at cART start in different country income groups, however did not stratify by age group and restricted to years where all age groups were represented.

In an analysis restricted to low- and middle-income countries with data for the year 2009, we modeled the country-level proportion of patients starting cART with severe immunodeficiency using a generalized linear mixed model. We chose the year 2009 because this was the most recent year where data from most countries were available. We examined the influence of age, gender, income group, and national pediatric cART coverage. These results are presented as adjusted odds ratios (OR) with 95% CI.

We used the dataset with imputed data for the main analysis. In sensitivity analyses, wefitted the model to complete data. Analyses were done in Stata 12 (Stata Corporation, CollegeStation, Texas, USA) and R version 3.0.2 (R Core Team, Vienna, Austria). The technical appendixprovides further details on the multiple imputation and smoothing (see Supplemental Digital Content 1, http://links.lww.com/). CD4 results are presented as observed or modeled median (IQR) CD4 count/% and proportion of children with severe immunodeficiency with 95% confidence intervals (CI).

Results

Descriptive analyses

Data of 36,125 children aged <16 years were submitted to the data center. Ninecountries with ≤200 children, seven with 201-1,000 children, seven with 1,001-5,000 children and two with >5,000 children contributed data (Figure 1). Ten children with missing gender were excluded;hence 36,115 children from 25 countries were included in descriptive analyses. Supplementary Figure S1 (Supplemental Digital Content 2, http://links.lww.com/) shows the inclusion of children in analyses.

Figure 1.

Figure 1

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Map of countries contributing patients to the collaborative analysis.

The number of children included from each country varied from 30 (Peru) to 11,830(Zambia) (Table 1). The percentage of girls was 49%overall (range across countries 40% [Senegal] to 54%[Botswana]). Median age at cART initiation was 5.2 years (range 10 months [Peru] to 9.1 years [Zimbabwe]). The median year of cART initiation was 2007 (range 1998 [USA] to 2008 [Peru, Vietnam, Zambia, Zimbabwe]). The percentage of children starting cART with severe immunodeficiency was 57% overall (20,619 children), range 22% (USA) to 83% (Peru) (Table 2).

Table 1.

Characteristics of 36,115 children starting cART by country and World Bank income group.

Country Number of children Median age in years Median calendar year of starting cART Calendar year range of available data Calendar years included in modeling*
Female Male Female Male Female Male
Low-income
Benin 33 38 2.9 4.8 2004 2005 2002 - 2006 excluded
Burkina Faso 72 89 6.3 6.3 2005 2004 2002 - 2007 excluded
Cambodia 166 175 5.9 6.1 2006 2006 2002 - 2010 2005 - 2009
Kenya 1859 2024 5.1 4.9 2007 2007 2002 - 2009 2003 - 2008
Malawi 729 682 7.5 7.8 2008 2007 2002 - 2010 2005 - 2010
Mali 321 470 4.0 4.0 2006 2005 2001 - 2008 2003 - 2008
Mozambique 567 607 3.2 3.3 2006 2006 1998 - 2010 2004 - 2008
Rwanda 95 90 7.0 7.0 2006 2006 2005 - 2009 2005 - 2009
Tanzania 172 152 8.2 6.6 2007 2007 2005 - 2008 2005 - 2008
Uganda 114 109 2.7 3.3 2005 2005 2003 - 2009 2003 - 2007
Zimbabwe 660 616 9.1 9.2 2008 2008 1999 - 2010 2004 - 2010
Overall
(IQR) 		4788 5052 5.7
(2.5 - 9.7) 		5.4
(2.4 - 9.2) 		2007
(2005 - 2008) 		2007
(2005 - 2008) 		1998 - 2010 2003 - 2010
Lower middle-income
Côte d'Ivoire 618 715 5.9 5.6 2005 2005 2003 - 2008 2004 - 2007
Ghana 164 161 5.7 5.2 2007 2006 2004 - 2009 2005 - 2008
India 42 57 8.0 7.2 2006 2006 2002 - 2010 excluded
Indonesia 63 79 2.0 1.8 2007 2007 1997 - 2010 2005 - 2009
Senegal 74 111 6.4 4.5 2006 2006 2000 - 2009 2005 - 2007
Vietnam 198 261 4.1 3.8 2008 2008 2005 - 2010 2005 - 2010
Zambia 5932 5898 5.7 5.2 2008 2008 2003 - 2010 2004 - 2010
Overall
(IQR) 		7091 7282 5.6
(2.1 - 9.7) 		5.1
(2.1 - 9.5) 		2008
(2006 - 2009) 		2007
(2006 - 2009) 		1997 - 2010 2004 - 2010
Upper middle-income
Botswana 28 24 8.3 8.3 2003 2004 1998 - 2007 excluded
Brazil 84 82 1.4 1.5 2006 2006 2003 - 2010 2004 - 2009
Malaysia 100 118 3.9 3.5 2006 2006 2000 - 2010 2005 - 2010
Peru 14 16 0.6 1.1 2008 2008 2006 - 2009 excluded
South Africa 4276 4386 4.0 3.9 2006 2006 1998 - 2010 2003 - 2010
Thailand 724 646 8.3 7.5 2005 2004 1999 - 2010 2003 - 2010
Overall
(IQR)		 5226 5272 4.6
(1.5 - 8.3)		 4.4
(1.5 - 7.6)		 2006
(2005 - 2007)		 2006
(2005 - 2007)		 1998 - 2010 2003 - 2010
High-income
USA 731 673 7.0 6.0 1998 1998 1995 - 2009 1995 - 2006
Overall
(IQR) 		731 673 7.0
(3 - 10) 		6.0
(3 - 9) 		1998
(1997 - 2000) 		1998
(1997 - 1999) 		1995 - 2009 1995 - 2006
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*

Calendar years were excluded from further analyses if there were <10 children starting cART with a CD4 cell measure. Five countries were excluded from further analyses because there were <50 children with a CD4 cell measure.

Table 2.

CD4 cell count and CD4% at start of cARTand the percentage of children starting cART with severe immunodeficiency by country and World Bank income group. Analyses based on 11,125 children aged 5 years or older with CD4 counts and 6,963 children below 5 years with CD4% data (complete case) and 34,706 children after imputation of missing data.

Country Percentage of children missing both CD4 count and CD4% measurements Median CD4 cell count at start of cART in cells/μl of children 5 years or older Median CD4% at start of cART of children younger than 5 years Percentage of children starting cART with severe immunodeficiency
Complete Case Imputed Data Complete Case Imputed Data Complete Case Imputed Data
Female Male Female Male Female Male Female Male Female Male Female Male Female Male
Low-income
Benin 3% 0% 78 181 excl. excl. NA NA excl. excl. 78% 63% excl. excl.
Burkina Faso 96% 96% 108 501 excl. excl. 20% 18% excl. excl. 67% 25% excl. excl.
Cambodia 2% 5% 180 222 170 174 12% 11% 12% 11% 71% 68% 70% 66%
Kenya 28% 27% 261 236 261 236 13% 12% 13% 13% 53% 57% 62% 64%
Malawi 48% 52% 253 209 253 198 18% 14% 17% 14% 49% 58% 50% 60%
Mali 4% 5% 174 157 172 167 20% 14% 17% 12% 61% 60% 55% 72%
Mozambique 20% 20% 299 319 296 325 14% 13% 14% 13% 58% 65% 67% 66%
Rwanda 25% 30% 293 259 265 256 NA NA 12% 13% 31% 32% 57% 54%
Tanzania 42% 41% 130 117 132 121 12% 20% 13% 21% 72% 70% 73% 66%
Uganda 28% 28% 692 464 635 471 12% 14% 12% 14% 59% 68% 61% 72%
Zimbabwe 22% 22% 186 174 186 174 12% 17% 11% 13% 57% 58% 69% 67%
Overall
(IQR) 		28% 28% 226
(89 - 404) 		206
(68 - 385) 		230
(94 - 405) 		205
(72 - 388) 		13%
(10 - 18) 		13%
(9 - 17) 		14%
(10 - 18) 		13%
(9 - 17) 		56%
(53 - 67) 		59%
(57 - 68) 		62%
(56 - 69) 		65%
(62 - 70)
Lower middleincome
Côte d'Ivoire 16% 19% 283 288 285 295 14% 14% 14% 15% 55% 53% 54% 52%
Ghana 38% 42% 174 108 155 125 14% 14% 12% 14% 57% 62% 67% 71%
India 7% 14% 192 197 excl. excl. 10% 12% excl. excl. 62% 59% excl. excl.
Indonesia 0% 6% 78 53 78 38 13% 7% 13% 6% 76% 85% 80% 87%
Senegal 47% 56% 78 261 65 297 28% 17% 19% 16% 56% 45% 64% 55%
Vietnam 9% 11% 111 122 104 112 11% 9% 11% 9% 72% 78% 71% 77%
Zambia 19% 17% 250 241 253 241 17% 15% 17% 15% 54% 57% 55% 59%
Overall
(IQR) 		19% 18% 246
(113 - 422) 		236
(100 - 414) 		251
(116 - 432) 		241
(103 - 422) 		16%
(11 - 22) 		14%
(9 - 20) 		16%
(11 - 22) 		15%
(10 - 20) 		55%
(55 - 72) 		57%
(53 - 78) 		56%
(54 - 73) 		59%
(54 - 80)
Upper middleincome
Botswana 18% 21% 216 326 excl. excl. 11% 30% excl. excl. 65% 53% excl. excl.
Brazil 0% 0% 440 514 452 514 22% 18% 22% 18% 46% 49% 42% 54%
Malaysia 20% 17% 50 103 49 121 17% 17% 17% 15% 73% 66% 74% 70%
Peru 0% 0% NA NA excl. excl. 11% 8% excl. excl. 79% 88% excl. excl.
South Africa 17% 19% 233 238 233 241 14% 14% 14% 14% 63% 64% 62% 63%
Thailand 16% 17% 107 64 110 69 13% 13% 14% 13% 64% 72% 65% 72%
Overall
(IQR)		 17% 18% 191
(49 - 380) 		183
(38 - 386) 		205
(58 - 396) 		205
(53 - 410) 		14%
(9 - 21) 		14%
(9 - 20.6) 		14%
(9 - 21) 		14%
(9 - 21) 		63%
(58 - 74) 		65%
(52 - 76) 		62%
(47 - 72) 		64%
(57 - 72)
High-income
USA 0% 0% 468 414 466 414 31% 28% 31% 28% 18% 26% 21% 28%
Overall
(IQR) 		0% 0% 468
(264 - 733) 		414
(175 - 695) 		466
(255 - 733) 		414
(171 - 698) 		31%
(22 - 40) 		28%
(19 - 34) 		31%
(22 - 40) 		28%
(19 - 34) 		18% 26% 21% 28%
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NA: not applicable (no data); excl: excluded.

Note: Complete case data includes all countries and calendar years. Imputed data only includes calendar years from individual countries with ≥10 children with available CD4 measures and countries with ≥50 children with available CD4 measures.

The median (IQR) age of children starting cART was 5.6 years (2.4-9.4) in LIC, 5.3(2.1-9.6) in LMIC, 4.5 (1.5-8.0) in UMIC and 6.0 (3.0-10.0) in HIC. The median CD4 count at cART initiation in children aged ≥5 years was 238 cells/μl in girls and 220 cells/μl in boys. In LIC it was 226 cells/μl (girls) and 206 cells/μl (boys). Corresponding values were higher in LMIC (246 cells/μl and 236 cells/μl, respectively) but lower in UMIC countries (191 cells/μl and 183 cells/μl, respectively). In the USA, the values were 468 cells/μl and 414 cells/μl, respectively. Similar patterns were evident for CD4% in children <5 years (Table 2). The percentage of children starting cART with severe immunodeficiency was 57% overall. Compared to LIC (58%) it was slightly lower in LMIC (56%), higher in UMIC (64%) and lower in the USA (22%). Apart from the comparison of age in LIC and HIC, all the above differences were statistically significant (p<0.05). However such significant differences are to be expected given the large number of observations.

Multiple imputation of missing CD4 measures

A total of 1,409 children were excluded from further analyses, either because theywerefrom Benin, Burkina Faso, India, Botswana or Peru, with <50 children with CD4 measures (413 children) or from calendar years with <10 children with CD4 measures (996 children). The multiple imputation of missing CD4 measures was thus based on 34,706 children. Compared to 6,528 children who had both measures missing, the 28,178 children with either CD4 count or percent measures available at cART initiation were older, more likely to be in WHO stage 1/2 or CDC Stage A/B, more likely to have information available on clinical stage, and less likely to be from a LIC (Table S1, Supplemental Digital Content 3, http://links.lww.com/). Both measures were missing in 19% of children overall, 25% in LIC, 18% in LMIC, 17% in UMIC and 0% in the USA (Table 2). Both measures were available in 31% ofchildren in LIC, 3% in LMIC, 13% in UMIC and 100% in the USA. Supplementary Figure S2 (Supplemental Digital Content 4, http://links.lww.com/) shows the proportion of children with available CD4 measure by country income and age groups.

CD4 counts were imputed for 3,014 (17%) of 17,860 children aged ≥5 yearswith no CD4 measure and for 4,017 (22%) children with only CD4% available. Similarly, CD4% values were imputed for 3,514 (21%) of 16,846 children aged <5 years with no CD4 measure and for 6,514 (39%) children who had a CD4 count available. Medians of imputed CD4 data (main analysis) and complete cases (sensitivity analysis) were generally similar (Table 2). The CD4 cell counts in UMIC increased somewhat after imputation of missing data, and the percentage of children starting cART with severe immunodeficiency increased in LIC. For children aged ≥5 years, the differences between observed and imputed CD4 values for individual countries ranged from -11cells/μl (boys from Mozambique) to +57cells/μl (girls from Uganda). For children aged <5 years, the differences ranged from -1% (boys from Kenya) to +4% (boys from Zimbabwe).

Temporal trends in CD4 measures

Data from low- and middle-income countries typically spanned the years 2003-2010 whereasdata from the USA were available for 1995-2006 only (Table 1). We first fitted models including separate smoothers for each combination of gender, age group and country income group. Gender did not improve model fit and was therefore removed. The final models included smoothers for each combination of age and country income group. Figure 2 shows modeled temporal trends in the prevalence of severe immunodeficiency at cART initiation; Figure 3 shows corresponding trends in median CD4 counts (children aged ≥5 years) or CD4% (children <5 years). In LIC the estimated percentage of children starting cART with severe immunodeficiency (as defined by WHO 2006 criteria) declined from 76% in 2004 to 63% in 2010. Corresponding figures for LMIC were from 77% to 66% and for UMIC from 75% to 58%. In the USA it decreased from 42% to 19% during 1996 to 2006 (Figure 2).

Figure 2.

Figure 2

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Severe immunodeficiency at start of combination antiretroviral therapy by age and country income group.

Results from generalized additive mixed effects model based 34,706 children after imputation of missing data. 95% confidence intervals are shown as shaded area.

Figure 3.

Figure 3

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Median CD4 cell count in children aged 5 years or older and median CD4% in children below 5 years of age at start of combination antiretroviral therapy by age and country income group.

Results from generalized additive mixed effects model based on 34,706 children after imputation of missing data. 95% confidence intervals are shown as shaded area.

In LIC, the median CD4 cell count at cART initiation in children aged ≥5 yearsincreased by 72% from 2004-2010, from 144 to 247 cells/μl. Corresponding increases for LMIC were 20% (115 to 138 cells/μl) and 52% in UMIC (101 to 153 cells/μl). The increase from 1996 to 2006 in the USA was 72% (254 to 398 cells/μl). In children aged <5 years, CD4% increased from 2004 to 2010 from 13% to 17% in LIC, from 11% to 15% in LMIC, and from 13% to 19% in UMIC. In the USA CD4% increased between 1996 and 2005 from 27% to 32% (Figure 3). Results of complete case analyses were similar (see Figure S3 and Figure S4, Supplemental Digital Content 5; 6, http://links.lww.com/).

Temporal trends in median age at cART initiation varied between country income groups (Figure S5, Supplemental Digital Content 7, http://links.lww.com/). There was no clear trend in median age at cART initiation in UMIC, while there was a decrease over time in LMIC (6.1 to 3.0 years) and LIC (6.5 to 4.6 years). In the USA, median age increased from 5.6 to 10.9 years (1996-2006).

Determinants of starting cART with severe immunodeficiency

Table 3 shows the adjusted OR of starting cART with severe immunodeficiency by gender, age group and income group in 2009 based on 4,121 children from four LIC (Cambodia, Malawi, Rwanda and Zimbabwe), three LMIC (Indonesia, Vietnam and Zambia) and four UMIC (Brazil, Malaysia, South Africa, Thailand). There was no difference in the probability of starting cART with severe immunodeficiency between genders but the ORs comparing the risk in infants with older children decreased up to age 5-11 years (OR 0.22; 95% CI 0.17-0.28) but increased in age group 12-15 years (OR 2.14; 95% CI 1.51-3.04). There was little evidence for a difference between country income groups, or across levels of national pediatric cART coverage. Results were similar in the complete case analysis (Table S2, Supplemental Digital Content 8, http://links.lww.com/).

Table 3.

Individual level and country level adjusted predictors for starting cART with severe immunodeficiency in 2009.

Results from generalized linear mixed model based on 4,121 children starting cART in 2009 from the countries Brazil, Cambodia, Indonesia, Malawi, Malaysia, Rwanda, South Africa, Thailand, Vietnam, Zambia and Zimbabwe with missing values imputed using multiple imputation.

Variable Adjusted odds ratio 95% confidence intervals
Gender
 Female 1.00
 Male 1.09 (0.92 - 1.29)
Age group (years)
 < 1 1.00
 1 - <3 0.79 (0.59 - 1.05)
 3 - <5 0.50 (0.35 - 0.71)
 5 - <12 0.22 (0.17 - 0.28)
 12 - <16 2.14 (1.51 - 3.04)
Country income level
 Low 1.00
 Lower middle 1.35 (0.63 - 2.88)
 Upper middle 0.79 (0.38 - 1.61)
National cART coverage (%)*
 < 40 1.00
 40 - <60 0.67 (0.3 - 1.49)
 60 - <80 1.37 (0.64 - 2.91)
 >= 80 0.82 (0.4 - 1.68)
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*

Based on a separate analysis that included national pediatric cART coverage instead of country income level.

Discussion

This global analysis of CD4 measures at cART initiation was based on over 35,000 children starting treatment in sub-Saharan Africa, South East Asia, Latin America, and North America. The percentage of children starting cART with severe immunodeficiency was substantially lower in the USA compared to other countries, with only small differences between lowincome and middle-income countries. The estimated proportion of children starting cART with severe immunodeficiency decreased everywhere over the study period. In 2010, however, approximately two-thirds of children in low- and middle-income countries still started cART with severe immunodeficiency.

Discussion of findings in the light of WHO HIV treatment guidelines

Our study confirms previous observations that many children in low and middle-income countries continue to start cART late.6,8,22-24 In 2010, 70% of children <2 years started cART with severe immunodeficiency despite WHO guidelines recommending early cART regardless of immunologic or clinical thresholds for all children in this age group.7 This may be partly due to delayed country-level implementation of WHO guidelines as well as poor access to early infant diagnosis (EID), slow turn-around time of test results, and limited cART availability for infants and young children.25 There was, however, wide variability in median CD4 values for countries in the same income group. Outside of the USA, the proportion of children starting cART with severe immunosuppression was similar across countries with different income levels. This may be due to substantial donor support for cART in LIC, in contrast to middle-income countries where national governments had to provide more finance for cART programs.

While the median age at cART initiation decreased over time in LIC and LMIC, it increased in the USA and there was no clear trend in UMIC although the confidence intervals were wide for all country income groups. Interpreting these trends is complex; the median age at cART initiation depends on the effectiveness of prevention of mother-to-child transmission (PMTCT) programs in reducing numbers of newly infected infants, capacity for EID and early cART as well as the backlog of older children not yet on therapy, which may be substantial.26,27 For example, the increasing age over time in the US is likely because effective PMTCT programs had largely eliminated new infant infections, with the few children initiating cART in later years being long term survivors who had remained relatively healthy without cART.

It is hoped that 2013 guidelines recommending universal cART for all children aged <5 years irrespective of CD4 or clinical stage will accelerate pediatric cART access by simplifying programs to a single recommendation for all children in this age group.9 These recommendations not only expand treatment eligibility but could potentially accelerate treatment initiation even for those who actually do have immunosuppression by removing the requirement for a CD4 measurement and consequent time lag while waiting for results before treatment is started. Changes in CD4 measures at ART initiation may therefore be a useful measure of responsiveness to guideline changes, with targets set for reductions in the proportion of children starting cART with severe immunosuppression.28

Role of infant and child diagnostic testing

The scale-up of PMTCT programs including antenatal opt-out HIV testing and EID testing may have contributed to gradually higher CD4 cell measures at cART initiation in infants. If more women were aware of their HIV status in pregnancy and enrolled in PMTCT programs with access to EID, there would be increasing likelihood of earlier testing of their HIVexposed infants. In addition, the scale-up of EID through dried blood spot HIV-PCR testing is encouraging.29-31 However, coverage remains low in many settings and postnatal PMTCT infant follow-up is frequently suboptimal,25,32 with many challenges such as lack of integration of PMTCT, HIV and child health programs, limited privacy in routine child health clinics, and slow turn-around times of HIV-PCR test results.33,34 HIV-infected older children are also frequently only identified one they have advanced disease, highlighting the importance of integrating provider-initiated HIV serological testing (cheap and easy to perform) at routine child health visits, especially in high prevalence settings.35,36

Poor access to cART for infants and children

Timely diagnosis of pediatric HIV does not necessarily result in timely cART. In national programs in Cambodia, Namibia, Senegal and Uganda, despite impressive EID scale-up, the proportion of infants identified as infected who subsequently intiated cART was <40% in all countries except Namibia.29 Key reasons for the diagnosis to treatment gap include HIV diagnostic tests and pediatric cART being located at separate sites without robust referral mechanisms between services, challenges with CD4 measurement to determine eligibility including access to tests, turn-around time and interpretation of results, as well as health care worker discomfort with treating children.29 In a review of studies including mostly older children, the proportion of cART eligible children that initiated treatment was as low as 40%.37 Approaches such as decentralization of pediatric cART to maternal and child health and clinics together with task-shifting and health care worker training in paediatric treatment and care may facilitate earlier cART initiation.38

Strengths and Limitations

This is a large pooled individualized patient-level dataset from multiple programs across the globe. In contrast to aggregate reporting data, it provides a more nuanced picture of progress towards pediatric cART access in a range of settings. However, we could not examine trends after 2010 because more recent data were not yet available from many sites. This is important as most lower income countries implemented the WHO 2010 recommendation of ART initiation irrespective of disease severity in children aged <2 years in 2011, and until recently there was limited access to EID.21, 31 There was substantial missing data on CD4 measures and clinical stage from low and middle income countries, so our estimates of median CD4 values may be biased. The high proportion of missing CD4 and clinical stage data is a concern as, for most of the data collection period, these measures were required to assess cART eligibility; their poor availability may indicate missed opportunities to initiate cART. In this respect the recent WHO recommendation of cART initiation in all children aged <5 years may improve pediatric cART access by eliminating the requirement for these measures prior to cART initiation, but may also preclude repeating analyses such as this one, making it more difficult to accurately monitor progress in access to cART.8 Data from some countries were limited to a small number of patients from a single clinic and so were excluded from analyses of time trends and predictors of CD4 at cART initiation as they are unlikely to be nationally representative. There were data from only one high-income country (USA), with relatively small numbers of children. In addition, only data up to 2005 from the USA could be analyzed precluding comparison with low and middle-income countries during the major period of scale-up in the latter regions.

Conclusion

Reductions in the proportion of children initiating cART with severe immunosuppression in low and middle income countries over time are encouraging but modest. Efforts to improve timely access to pediatric HIV diagnosis and cART should remain a global public health priority.

Supplementary Material

Supplemental Digital Content

Acknowledgments

We are grateful to all children, care givers and data managers involved in the participating cohorts and treatment programs. The African regions of the International epidemiologic Databases to Evaluate AIDS (IeDEA) are supported by the National Cancer Institute (NCI), the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) and the National Institute of Allergy And Infectious Diseases (NIAID) as part of the International epidemiologic Databases to Evaluate AIDS (IeDEA) (Grants 5U01AI069919-04, 5U01-AI069924-05, 1U01 AI069927, U01AI069911-01). The TREAT Asia HIV Observational Database, TREAT Asia Studies to Evaluate Resistance, and the Australian HIV Observational Database are initiatives of TREAT Asia, a program of amfAR, The Foundation for AIDS Research, with support from the Dutch Ministry of Foreign Affairs through a partnership with Stichting Aids Fonds, and NIAID, NICHD and NCI, as part of IeDEA (U01AI069907). Queen Elizabeth Hospital and the Integrated Treatment Centre received additional support from the Hong Kong Council for AIDS Trust Fund. The Kirby Institute is funded by the Australian Government Department of Health and Ageing, and is affiliated with the Faculty of Medicine, University of New South Wales. The NICHD Site Development Initiative (NISDI) was funded by the NIH and NICHD (contracts N01-HD-3-3345 and N01-HD-8-0001). The Pediatric HIV/AIDS Cohort Study (PHACS) is supported by NICHD with co-funding from the National Institute on Drug Abuse (NIDA), NIAID, the Office of AIDS Research, the National Institute of Mental Health, the National Institute of Neurological Disorders and Stroke, the National Institute on Deafness and Other Communication Disorders, the National Heart Lung and Blood Institute, the National Institute of Dental and Craniofacial Research, and the National Institute on Alcohol Abuse and Alcoholism, through cooperative agreements with the Harvard University School of Public Health (HD052102, 3 U01 HD052102-05S1, 3 U01 HD052102-06S3) and the Tulane University School of Medicine (HD052104, 3U01HD052104-06S1). Support for the International Maternal Pediatric Adolescent AIDS Clinical Trials Group (IMPAACT) 219C study is provided by NIAID (U01 AI068632) and NICHD (contract N01-3-3345 and HHSN267200800001C). This work was also supported by the Statistical and Data Analysis Center at Harvard School of Public Health, under the NIAID cooperative agreement #5 U01 AI41110 with the Pediatric AIDS Clinical Trials Group (PACTG) and #1 U01 AI068616 with the IMPAACT Group. The content of this publication is solely the responsibility of the authors and does not necessarily represent the official views of any of the institutions and funders mentioned.

Funding sources: The African regions of the International epidemiologic Databases to Evaluate AIDS (IeDEA) are supported by the National Cancer Institute (NCI), the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) and the National Institute of Allergy And Infectious Diseases (NIAID) as part of the International epidemiologic Databases to Evaluate AIDS (IeDEA) (Grants 5U01AI069919-04, 5U01-AI069924-05, 1U01 AI069927, U01AI069911-01). The TREAT Asia HIV Observational Database, TREAT Asia Studies to Evaluate Resistance, and the Australian HIV Observational Database are initiatives of TREAT Asia, a program of amfAR, The Foundation for AIDS Research, with support from the Dutch Ministry of Foreign Affairs through a partnership with Stichting Aids Fonds, and NIAID, NICHD and NCI, as part of IeDEA (U01AI069907). Queen Elizabeth Hospital and the Integrated Treatment Centre received additional support from the Hong Kong Council for AIDS Trust Fund. The Kirby Institute is funded by the Australian Government Department of Health and Ageing, and is affiliated with the Faculty of Medicine, University of New South Wales. The NICHD Site Development Initiative (NISDI) was funded by the NIH and NICHD (contracts N01-HD-3-3345 and N01-HD-8-0001). The Pediatric HIV/AIDS Cohort Study (PHACS) was supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development with co-funding from the National Institute on Drug Abuse, the National Institute of Allergy and Infectious Diseases, the Office of AIDS Research, the National Institute of Mental Health, the National Institute of Neurological Disorders and Stroke, the National Institute on Deafness and Other Communication Disorders, the National Heart Lung and Blood Institute, the National Institute of Dental and Craniofacial Research, and the National Institute on Alcohol Abuse and Alcoholism, through cooperative agreements with the Harvard University School of Public Health (HD052102, 3 U01 HD052102-05S1, 3 U01 HD052102-06S3) and the Tulane University School of Medicine (HD052104, 3U01HD052104-06S1). Support for the International Maternal Pediatric Adolescent AIDS Clinical Trials Group (IMPAACT) 219C study is provided by the NIAID (U01 AI068632) and NICHD (contract N01-3-3345 and HHSN267200800001C). This work was also supported by the Statistical and Data Analysis Center at Harvard School of Public Health, under the NIAID cooperative agreement #5 U01 AI41110 with the Pediatric AIDS Clinical Trials Group (PACTG) and #1 U01 AI068616 with the IMPAACT Group.

Footnotes

This data was presented at the 20th Conference on Retroviruses and Opportunistic Infections March 3-7, 2013, Atlanta, USA

Note: The conclusions and opinions expressed in this article are those of the authors and do not necessarily reflect those of the National Institutes of Health or U.S. Department of Health and Human Services or any of the other funders.

References

  • 1.World Health Organization UNAIDS UNICEF. Global HIV/AIDS response: epidemic update and health sector progress towards universal access: progress report 2011. 2011 http://www.who.int/hiv/pub/progress_report2011/en/index.html.
  • 2.World Health Organization. [Accessed 21 July 2014];Global update on the health sector response to HIV, 2014. 2014 http://www.who.int/hiv/pub/progressreports/en/
  • 3.Bolton-Moore C, Mubiana-Mbewe M, Cantrell RA, Chintu N, Stringer EM, Chi BH, Sinkala M, Kankasa C, Wilson CM, Wilfert CM, Mwango A, Levy J, Abrams EJ, Bulterys M, Stringer JS. Clinical outcomes and CD4 cell response in children receiving antiretroviral therapy at primary health care facilities in Zambia. JAMA: the journal of the American Medical Association. 2007;298:1888–1899. doi: 10.1001/jama.298.16.1888. [DOI] [PubMed] [Google Scholar]
  • 4.Sutcliffe CG, van Dijk JH, Bolton C, Persaud D, Moss WJ. Effectiveness of antiretroviral therapy among HIV-infected children in sub-Saharan Africa. Lancet Infect Dis. 2008;8:477–489. doi: 10.1016/S1473-3099(08)70180-4. [DOI] [PubMed] [Google Scholar]
  • 5.Davies MA, Keiser O, Technau K, Eley B, Rabie H, Van Cutsem G, Giddy J, Wood R, Boulle A, Egger M, Moultrie H. Outcomes of the South African National Antiretroviral Treatment Programme for children: the IeDEA Southern Africa collaboration. S Afr Med J. 2009;99:730–737. [PMC free article] [PubMed] [Google Scholar]
  • 6.Leroy V, Malateste K, Rabie H, Lumbiganon P, Ayaya S, Dicko F, Davies MA, Kariminia A, Wools-Kaloustian K, Aka E, Phiri S, Aurpibul L, Yiannoutsos C, Signate-Sy H, Mofenson L, Dabis F. 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;62:208–219. doi: 10.1097/QAI.0b013e31827b70bf. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.World Health Organization. Antiretroviral therapy of HIV infection in infants and children: towards universal access: recommendations for a public health approach - 2010 revision. 2010:1–194. Available at: http://www.who.int/hiv/pub/paediatric/infants2010/en/index.html. [PubMed]
  • 8.Davies M, May M, Bolton-Moore C, Chimbetete C, Eley B, Garone D, Giddy J, Moultrie H, Ndirangu J, Phiri S, Rabie H, Technau K, Wood R, Boulle A, Egger M, Keiser O. Prognosis of children with HIV-1 infection starting antiretroviral therapy in Southern Africa: a collaborative analysis of treatment programs. Pediatr Infect Dis J. 2013 doi: 10.1097/INF.0000000000000214. epublished ahead of print. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.World Health Organization. Consolidated guidelines on the Use of Antiretroviral Drugs for Treating and Preventing HIV Infection. Summary of key features and recommendations. 2013 http://www.who.int/hiv/pub/guidelines/arv2013/short_summary/en/index.html. [PubMed]
  • 10.Wettstein C, Mugglin C, Egger M, Blaser N, Salazar L, Estill J, Bender N, Davies MA, Wandeler G, Keiser O. Missed Opportunities to Prevent Mother-to-Child-Transmission in sub-Saharan Africa: Systematic Review and Meta-Analysis. AIDS. 2012 doi: 10.1097/QAD.0b013e328359ab0c. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Gange SJ, Kitahata MM, Saag MS, Bangsberg DR, Bosch RJ, Brooks JT, Calzavara L, Deeks SG, Eron JJ, Gebo KA, Gill MJ, Haas DW, Hogg RS, Horberg MA, Jacobson LP, Justice AC, Kirk GD, Klein MB, Martin JN, McKaig RG, Rodriguez B, Rourke SB, Sterling TR, Freeman AM, Moore RD. Cohort profile: the North American AIDS Cohort Collaboration on Research and Design (NA-ACCORD) International Journal of Epidemiology. 2007;36:294–301. doi: 10.1093/ije/dyl286. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.McGowan CC, Cahn P, Gotuzzo E, Padgett D, Pape JW, Wolff M, Schechter M, Masys DR. Cohort Profile: Caribbean, Central and South America Network for HIV research (CCASAnet) collaboration within the International Epidemiologic Databases to Evaluate AIDS (IeDEA) programme. International Journal of Epidemiology. 2007;36:969–976. doi: 10.1093/ije/dym073. [DOI] [PubMed] [Google Scholar]
  • 13.Zhou J, Kumarasamy N, Ditangco R, Kamarulzaman A, Lee CK, Li PC, Paton NI, Phanuphak P, Pujari S, Vibhagool A, Wong WW, Zhang F, Chuah J, Frost KR, Cooper DA, Law MG Database TAHO. The TREAT Asia HIV Observational Database: baseline and retrospective data. J Acquir Immune Defic Syndr. 2005;38:174–179. doi: 10.1097/01.qai.0000145351.96815.d5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.The IeDEA Pediatric Working Group. A survey of paediatric HIV programmatic and clinical management practices in Asia and sub-Saharan Africa-the International epidemiologic Databases to Evaluate AIDS (IeDEA) J Int AIDS Soc. 2013;16:17998. doi: 10.7448/IAS.16.1.17998. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Hazra R, Stoszek SK, Hance LF, Pinto J, Marques H, Peixoto M, Alarcon J, Mussi-Pinhata M, Serchuck L. Cohort Profile: NICHD International Site Development Initiative (NISDI): a prospective, observational study of HIV-exposed and HIV-infected children at clinical sites in Latin American and Caribbean countries. Int J Epidemiol. 2009;38:1207–1214. doi: 10.1093/ije/dyn239. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Van Dyke RB, Patel K, Siberry GK, Burchett SK, Spector SA, Chernoff MC, Read JS, Mofenson LM, Seage GR, 3rd, Pediatric HIVACS Antiretroviral treatment of US children with perinatally acquired HIV infection: temporal changes in therapy between 1991 and 2009 and predictors of immunologic and virologic outcomes. J Acquir Immune Defic Syndr. 2011;57:165–173. doi: 10.1097/QAI.0b013e318215c7b1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Patel K, Ming X, Williams PL, Robertson KR, Oleske JM, Seage GR, 3rd International Maternal Pediatric Adolescent ACTCST. Impact of HAART and CNS-penetrating antiretroviral regimens on HIV encephalopathy among perinatally infected children and adolescents. AIDS. 2009;23:1893–1901. doi: 10.1097/QAD.0b013e32832dc041. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.The World Bank. [Accessed 12.12];How we classify countries. http://data.worldbank.org/about/country-classifications.
  • 19.World Health Organization. Antiretroviral therapy for HIV Infection in adults and adolescents in resource-limited settings: towards universal access. Recommendations for a public health approach. 2006 http://www.who.int/hiv/pub/guidelines/artadultguidelines.pdf.
  • 20.World Health Organization. Towards universal access Scaling up priority HIV/AIDS interventions in the health sector. Progress Report 2010. 2010 http://www.who.int/hiv/pub/2010progressreport/en/index.html.
  • 21.Rubin DB. Multiple Imputation for Nonresponse in Surveys. New York: John Wiley; 1987. [Google Scholar]
  • 22.Fatti G, Bock P, Eley B, Mothibi E, Grimwood A. Temporal trends in baseline characteristics and treatment outcomes of children starting antiretroviral treatment: an analysis in four provinces in South Africa, 2004-2009. J Acquir Immune Defic Syndr. 2011;58:e60–67. doi: 10.1097/QAI.0b013e3182303c7e. [DOI] [PubMed] [Google Scholar]
  • 23.Peacock-Villada E, Richardson BA, John-Stewart GC. Post-HAART outcomes in pediatric populations: comparison of resource-limited and developed countries. Pediatrics. 2011;127:e423–441. doi: 10.1542/peds.2009-2701. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.McNairy ML, Lamb MR, Carter RJ, Fayorsey R, Tene G, Mutabazi V, Gusmao E, Panya M, Sheriff M, Abrams EJ. Retention of HIV-infected children on antiretroviral treatment in HIV care and treatment programs in Kenya, Mozambique, Rwanda, and Tanzania. J Acquir Immune Defic Syndr. 2013;62:e70–81. doi: 10.1097/QAI.0b013e318278bcb0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.UNAIDS. 2013 Progress report on the global plan towards the elimination of new HIV infection in children by 2015 and keeping their mothers alive. [Accessed 25 June 2013];2013 http://www.unaids.org/en/media/unaids/contentassets/documents/unaidspublication/2013/20130625_progress_global_plan_en.pdf.
  • 26.Ferrand R, Lowe S, Whande B, Munaiwa L, Langhaug L, Cowan F, Mugurungi O, Gibb D, Munyati S, Williams BG, Corbett EL. Survey of children accessing HIV services in a high prevalence setting: time for adolescents to count? Bull World Health Organ. 2010;88:428–434. doi: 10.2471/BLT.09.066126. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Ferrand RA, Munaiwa L, Matsekete J, Bandason T, Nathoo K, Ndhlovu CE, Munyati S, Cowan FM, Gibb DM, Corbett EL. Undiagnosed HIV infection among adolescents seeking primary health care in Zimbabwe. Clin Infect Dis. 2010;51:844–851. doi: 10.1086/656361. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Johnson LF, Boulle A. How should access to antiretroviral treatment be measured? Bull World Health Organ. 2011;89:157–160. doi: 10.2471/BLT.10.080911. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Chatterjee A, Tripathi S, Gass R, Hamunime N, Panha S, Kiyaga C, Wade A, Barnhart M, Luo C, Ekpini R. Implementing services for Early Infant Diagnosis (EID) of HIV: a comparative descriptive analysis of national programs in four countries. BMC Public Health. 2011;11:553. doi: 10.1186/1471-2458-11-553. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Sherman GG, Cooper PA, Coovadia AH, Puren AJ, Jones SA, Mokhachane M, Bolton KD. Polymerase chain reaction for diagnosis of human immunodeficiency virus infection in infancy in low resource settings. Pediatr Infect Dis J. 2005;24:993–997. doi: 10.1097/01.inf.0000187036.73539.8d. [DOI] [PubMed] [Google Scholar]
  • 31.Yapo V, d'Aquin Toni T, Desmonde S, Amani-Bosse C, Oga M, Lenaud S, Menan H, Timite-Konan M, Leroy V, Rouzioux C. Evaluation of dried blood spot diagnosis using HIV1-DNA and HIV1-RNA Biocentric assays in infants in Abidjan, Cote d'Ivoire. The Pedi-Test DBS ANRS 12183 Study. J Virol Methods. 2013;193:439–445. doi: 10.1016/j.jviromet.2013.07.011. [DOI] [PubMed] [Google Scholar]
  • 32.Sibanda E, Weller I, Hakim J, Cowan F. The magnitude of loss to follow-up of HIVexposed infants along the prevention of mother-to-child HIV transmission continuum of care: a systematic review and meta-analysis. AIDS. 2013 doi: 10.1097/QAD.0000000000000027. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Dube Q, Dow A, Chirambo C, Lebov J, Tenthani L, Moore M, Heyderman RS, Van Rie A. Implementing early infant diagnosis of HIV infection at the primary care level: experiences and challenges in Malawi. Bull World Health Organ. 2012;90:699–704. doi: 10.2471/BLT.11.100776. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Seidenberg P, Nicholson S, Schaefer M, Semrau K, Bweupe M, Masese N, Bonawitz R, Chitembo L, Goggin C, Thea DM. Early infant diagnosis of HIV infection in Zambia through mobile phone texting of blood test results. Bull World Health Organ. 2012;90:348–356. doi: 10.2471/BLT.11.100032. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Rollins N, Mzolo S, Moodley T, Esterhuizen T, van Rooyen H. Universal HIV testing of infants at immunization clinics: an acceptable and feasible approach for early infant diagnosis in high HIV prevalence settings. AIDS. 2009;23:1851–1857. doi: 10.1097/QAD.0b013e32832d84fd. [DOI] [PubMed] [Google Scholar]
  • 36.Weigel R, Kamthunzi P, Mwansambo C, Phiri S, Kazembe PN. Effect of providerinitiated testing and counselling and integration of ART services on access to HIV diagnosis and treatment for children in Lilongwe, Malawi: a pre- post comparison. BMC Pediatrics. 2009;9:80. doi: 10.1186/1471-2431-9-80. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Mugglin C, Wandeler G, Estill J, Egger M, Bender N, Davies MA, Keiser O. Retention in Care of HIV-Infected Children from HIV Test to Start of Antiretroviral Therapy: Systematic Review. PLoS One. 2013;8:e56446. doi: 10.1371/journal.pone.0056446. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Penazzato M, Davies M, Apollo T, Negussie E, Ford N. Task shifting for the delivery of pediatric antiretroviral treatment: a systematic review. J Acquir Immune Defic Syndr. 2013 doi: 10.1097/QAI.0000000000000024. epublished ahead of print. [DOI] [PubMed] [Google Scholar]

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