Scale-up and expansion of antiretroviral therapy (ART) for people living with HIV (PLHIV) have been a global priority for more than 15 years.
We describe PLHIV at enrollment in care and ART initiation in Ethiopia, Kenya, Mozambique and Tanzania from 2005–2014 and report on enrollment location, CD4 count and loss to follow-up (LTF), death, and combined attrition (LTF and death) pre- and post-ART initiation over time. Pre-ART outcomes were estimated using competing risk and post-ART using Kaplan-Meier estimators; LTF defined as no visit within six months pre-ART and 12 months after ART start.
From 2005–2014, 884,328 PLHIV enrolled in care at 350 health facilities, median age was 32.0 years (interquartile range [IQR] 26.0–42.0), and majority were female (66.5%). The proportion of PLHIV enrolled at primary and rural facilities increased from 12.9% and 15.3% in 2005–2006 to 43.5% and 41.7% in 2013–2014 (p<0.0001). Median CD4+ cell count at enrollment increased from 171 cell/mm3 in 2005–2006 (IQR 71–339) to 289 cell/mm3 in 2013–2014 (IQR 133–485) (p<0.0001). A total of 460,758 (57.4%) PLHIV initiated treatment. Cumulative risk of LTF for PLHIV prior to ART initiation 12 months after enrollment was 33.5% (95%CI 33.36–33.58) and 21.98% (95%CI 21.9–22.1) after ART initiation. Pregnant women and the youngest PLHIV group had the highest attrition after ART initiation, at 24 months 40.8% (95%CI 40.1–41.6) of pregnant women and 47.4% (95%CI 46.4–48.4) of PLHIV 15–19 years were not retained. Attrition at 12 months after enrollment among PLHIV regardless of ART status was 38.5% (95%CI 38.4–38.6).
Over 10 years of HIV scale-up in four sub-Saharan African countries, close to a million PLHIV were enrolled in care increasingly at rural and primary facilities with increasing CD4 count. Loss to follow-up from HIV care remains alarmingly high, particularly among pregnant women and younger PLHIV.
Citation: Teasdale CA, Abrams EJ, Yuengling KA, Lamb MR, Wang C, Vitale M, et al. (2020) Expansion and scale-up of HIV care and treatment services in four countries over ten years. PLoS ONE 15(4): e0231667. https://doi.org/10.1371/journal.pone.0231667
Editor: Kwasi Torpey, University of Ghana College of Health Sciences, GHANA
Received: February 10, 2020; Accepted: March 27, 2020; Published: April 16, 2020
Copyright: © 2020 Teasdale et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The data are owned by the governments of each country (Ethiopia, Kenya, Mozambique and Tanzania) who have not agreed to make the data publicly available. The CDC office in each country has copies of the data sets and requests can be made those those offices. For access to the data, please contact ICAP at Columbia University which will facilitate data access (email: firstname.lastname@example.org or email@example.com).
Funding: This work was supported by the President’s Emergency Plan for AIDS Relief (PEPFAR) through the Centers for Disease Control and Prevention under the terms of Cooperative Agreement Number 5U62PS223540 and 5U2GPS001537. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of PEPFAR or the Centers for Disease Control and Prevention. The authors were not paid by any outside entity to write this paper.
Competing interests: The authors have declared that no competing interests exist.
Remarkable progress has been achieved in the scale-up of antiretroviral therapy (ART) and health services for people living with HIV (PLHIV) in resource limited settings (RLS).  In 2004, out of the estimated 38 million PLHIV worldwide, fewer than 400,000 in low and middle-income countries were on ART, only 7% of those eligible for treatment at the time.  As of mid-2019, among the estimated 37.9 million PLHIV, 24.5 million were on ART (64.6%), and there has been a 55% decline in AIDS deaths from the peak of 1.2 million in 2004 to 770,000 in 2018, largely due to the expansion of HIV care and antiretroviral treatment. 
The epicenter of the epidemic remains in sub-Saharan Africa (SSA), specifically Eastern and Southern Africa which are home to 54.4% of all PLHIV worldwide (20.6 million PLHIV).  Many countries in this region have made significant progress in expanding HIV testing and treatment services. Data from the Population-Based HIV Impact Assessments (PHIA) conducted in multiple African countries have highlighted the incredible success in HIV scale-up and progress towards the ambitious 2020 UNAIDS 90-90-90 targets for HIV testing, ART initiation, and viral load suppression.  In Eswatini, as one example, 87% of adult PLHIV identified through the household testing survey reported knowledge of their HIV status, 89% self-reported being on ART, and 91% were virally suppressed (<1,000 copies/mL).  Despite this progress, challenges persist in identifying, enrolling, and retaining all PLHIV in HIV care. Malawi, Zambia and Zimbabwe PHIA data showed that up to half of previously undiagnosed adults had CD4+ <350 cells/mm3 and that men were significantly more likely to have advanced disease at diagnosis.  UNAIDS and PHIA data also demonstrate persistent sex gaps in uptake of ART with 68% of women on treatment in 2018 compared to 55% of men. [3,7] In addition, HIV treatment programs continue to struggle to retain patients in follow-up. A recent meta-analysis of ART retention data found that only 65% of PLHIV starting ART in Africa were still on treatment after 36 months.  These findings underscore the ongoing challenges of continuing to expand HIV testing and treatment services while also striving to improve retention of PLHIV and achieve optimal outcomes.
We examined a large patient level dataset from 350 HIV care and treatment facilities in Ethiopia, Kenya, Mozambique, and Tanzania from 2005 through 2014 to describe the characteristics of PLHIV at entry to HIV care and at ART initiation over time. We also estimate loss to follow-up (LTF), mortality and combined attrition (LTF and death) over the ten year period. This analysis is one of the largest to date of PLHIV enrolling in routine HIV care and treatment services, and provides important insights into the changes over the initial decade of HIV treatment scale-up and the ongoing challenges faced by HIV programs across four severely affected countries.
We examined routinely collected patient-level data from health facilities in Ethiopia, Kenya, Mozambique, and Tanzania as part of the Identifying Optimal Models of HIV Care in Africa study, funded by President’s Emergency Plan for AIDS Relief (PEPFAR) through the US Centers for Disease Control and Prevention (CDC). In partnership with the Ministries of Health in each country, all health facilities received support from ICAP at Columbia University and offered a standard package of services, including HIV testing, pre-ART and ART care, and prevention and treatment for opportunistic infections, per each country’s national guidelines. National ART eligibility guidelines in each country changed over the period of observation and are summarized in S1 Table. Ethics and administrative approvals were obtained from the Columbia University Medical Center institutional review board (IRB) and the Associate Director of Science Office at the CDC, as well as from review boards in each country.
The study population included all adult PLHIV ≥15 years of age who enrolled at the health facilities from January 1, 2005 through December 31, 2014. Patients who enrolled in care <12 months prior to the last date of data collection at each health facility were excluded. At all facilities, medical record data from routine care visits were entered into on-site electronic databases by trained data capturers with data quality support from ICAP. Loss to follow-up (LTF) was defined as not having a recorded outcome of death or transfer out and before ART initiation (pre-ART) as not having a clinic visit for >12 months and >6 months after ART initiation. Data on deaths and documented transfer to other facilities were ascertained from facility records. Time to LTF or death was calculated from the date of ART initiation to the date of death (if available) or the last visit date.
We describe characteristics of PLHIV at enrollment in HIV care and at time of ART initiation based on year of enrollment and country including age, sex, point of entry, CD4 cell count (CD4+), and WHO HIV disease stage (measured up to 90 days prior and 30 days after). Cochran-Armitage tests for proportions and Kruskal-Wallis tests for medians were used to compare characteristics of PLHIV at enrollment and ART initiation in the periods 2005–2006 and 2013–2014. We report cumulative incidence of LTF, death, and combined attrition (LTF and death) before (pre-ART) and following ART initiation among patients who were ART-naïve at enrollment (patients reporting prior ART or current ART at time of enrollment were excluded from retention analyses). We also analyzed LTF, death, and combined attrition for all enrolled patients regardless of ART status in order to measure overall lack of retention at enrollment facilities among all PLHIV entering care. Survival analyses were conducted using competing risk estimators for pre-ART outcomes (treating ART initiation as a competing risk for pre-ART death and combined attrition, and ART initiation and death as competing risks for pre-ART LTF). For outcomes after ART initiation and for the analysis of all enrolled patients, Kaplan-Meier estimators were used. Unadjusted sub-distributional hazards (pre-ART) and Cox proportional hazards models (following ART initiation) were used to compare cumulative incidence by groups. Statistical analyses were performed in SAS 9.3 and Stata 12.
A total of 884,328 patients enrolled in care at the 350 health facilities in the four countries between 2005 and 2014 (Table 1). The median duration of data collection at the individual facilities included in the analysis was 8 years (interquartile range (IQR) 7–9). Over time, more patients enrolled at primary health facilities; among all PLHIV 12.9% enrolled at primary health facilities in 2005–2006 compared to 43.5% in 2013–2014 (p<0.0001) (Fig 1). The proportion of PLHIV enrolled at rural health facilities also increased from 15.3% of patients in 2005–2006 to 41.7% in 2013–2014 (p<0.0001). The median age of all PLHIV at enrollment was 32.0 years (interquartile range [IQR] 26.0–42.0) with the proportion of patients 15–19 years increasing from 2.8% (2005–2006) to 6.5% (2013–2014) (p<0.0001). The majority were female (66.5%) and the proportion of those enrolled during a pregnancy increased from 4.8% in 2005–2006 to 25.0% in 2013-2014(p<0.0001) (Table 1). Median CD4+ at enrollment for all PLHIV increased from 171 cell/mm3 in 2005–2006 (IQR 71–339) to 289 cell/mm3 in 2013–2014 (IQR 133–485) (p<0.0001) (49.4% missing) (Fig 2). Among PLHIV with WHO stage at enrollment (79.9%), the proportion with WHO stage III or IV at enrollment decreased over time from 61.4% in 2005–2006 to 33.9% in 2013–2014 (p<0.0001) (Table 1). The proportion of PLHIV who were eligible for ART at entry to care according to prevailing national guidelines increased over time from 30.6% in 2005–2006 to 47.4% in 2013–2014 (p<0.0001). Overall, 18.2% of PLHIV had no visits recorded at the facility after the date of enrollment. S2 Table has characteristics of PLHIV at enrollment by country.
Among the 802,348 ART-naïve PLHIV enrolled in care, 460,758 (57.4%) initiated treatment. There was an increase in the proportion of PLHIV starting ART at primary health facilities and those in rural areas (Table 1). The median age at ART initiation was 34 years (IQR: 28–42) and the majority (65.2%) were female. The proportion of women pregnant at ART initiation increased from 7.3% in 2005–2006 to 38.1% in 2013–2014 (p<0.0001). Median CD4+ increased from 141 cells/mm3 (IQR 65–215) in 2005–2006 to 227 cells/mm3 (IQR 109–350) in 2013–2014 (p<0.0001) (29.8% missing). Over time fewer PLHIV were WHO stage III/IV at ART initiation; 73.3% in 2005–2006 compared to 42.7% in 2013–2014 (p<0.0001). Median time from enrollment to ART initiation decreased over time from 52 days (IQR 9–231) to 16 days (IQR 0–55) from 2005–2006 to 2013–2014, respectively (p<0.0001) (Table 1). S3 Table has characteristics at ART initiation by country.
The cumulative risk of LTF for patients in care prior to ART initiation at 12, 24, and 36 months after enrollment in care was 33.5% (95%CI 33.4–33.6), 36.0% (95%CI 35.9–36.1) and 37.2% (95%CI 37.1–37.3), respectively (Table 2). Overall documented mortality at 12, 24, and 36 months after enrollment in care among PLHIV pre-ART was roughly 2% and decreased over time with highest mortality observed in Tanzania (5.0%, 95%CI 4.8–5.1), 36 months. Combined pre-ART attrition including LTF and death was 34.9% (95%CI 34.8–35.0, 37.5% (95%CI 37.4–37.6) and 38.7% (95%CI 38.6–38.8) at 12, 24 and 36 months, respectively, and decreased from 2005–2006 to 2013–2014 (p<0.0001). Women pregnant at enrollment and PLHIV 15–19 years of age had highest pre-ART attrition; 51.3% (95%CI 50.9–51.6) and 57.2% (95%CI 56.7–57.8) were not retained at 24 months, respectively (Table 2).
LTF among PLHIV who initiated ART was 22.0% (95%CI 21.9–22.1), 29.5% (95%CI 29.4–29.7) and 35.4 (95%CI 35.3–35.6) at 12, 24, and 36 months, respectively (Table 3). LTF after ART initiation increased over time from 21.7% (95%CI 21.4–22.1) LTF by 24 months among PLHIV who enrolled in care 2005–2006 compared to 34.0% (95%CI 33.4–34.7) in 2013–2014 (p<0.0001). Loss to follow-up after ART initiation was highest in Mozambique where 45.2% (95%CI 44.9–45.5) of PLHIV who started treatment had been lost by 36 months. Men had higher attrition after ART start compared to women; at 24 months after ART initiation, 37.8% (95%CI 37.6–38.1) of men were not retained compared to 31.9% (95%CI 31.3–3.6) of women (p<0.0001). Pregnant women and the youngest PLHIV group had the highest attrition after ART initiation; at 24 months 40.8% (95%CI 40.1–41.6) of pregnant women and 47.4% (95%CI 46.4–48.4) of PLHIV 15–19 years were not retained (Table 3).
Overall attrition (LTF and death) among all enrolled PLHIV regardless of ART status was 38.5 (95%CI 38.4–38.6) at 12 months, 44.4% (95%CI 44.3–44.5) at 24 months and 48.2% (95%CI 48.1–48.3) at 36 months (Table 4). Among all PLHIV enrolled 2005–2006, 48.0% (95%CI 47.7–48.3) were not retained in care at 36 months compared to 45.6% (95%CI 45.1–46.0) of those PLHIV enrolled 2013–2014 (p<0.0001). Attrition was higher among PLHIV with CD4+ >500 (39.9%, 95%CI 39.6–40.3, 24 months) compared to those with CD4<200 at enrollment (35.0%, 95%CI 34.8–35.2) (p<0.0001). Almost half of all men and women enrolled were not retained but among women who were pregnant at enrollment, 58.5 (95%CI 58.1–58.9) were not retained at 36 months (Table 4). Almost two-thirds (64.0%, 95%CI 63.5–64.6) of PLHIV 15–19 years of age and more than half (54.5%, 95%CI 54.3–54.7) of PLHIV 20–29 years were not retained at 36 months.
This analysis of almost one million PLHIV enrolled in care at 350 health facilities over ten years across four countries in Eastern and Southern Africa reflects the evolution of the HIV response over that decade, the progress made in expanding access to more populations with HIV, as well as the remaining challenges. By the end of the first decade of rapid ART expansion, a higher proportion of PLHIV entered care and started ART at primary health facilities and in rural areas, demonstrating successful decentralization of HIV services. Women continued to represent the majority of patients enrolled in care and starting ART, with a large increase in pregnant women starting ART over time. Median CD4+ at enrollment, while increasing over time, remained low at 289 cell/mm3 in 2013–2014. Attrition was high–roughly 20% of all PLHIV enrolled in care had no further recorded visits and almost 35% of PLHIV not yet on ART were LTF or had died within 12 months. While early attrition was lower among PLHIV after starting ART compared to those not on treatment, by 36 months estimates for attrition for patients not yet on ART and those on treatment were around 40%. In the latest period of observation, 2013–2014, pre-ART attrition had declined to 26% at 36 months but for PLHIV on ART, it had increased from 34% to 41%. Overall, regardless of ART status, almost half (48%) of PLHIV across the four countries were not retained at the facilities where they enrolled at 3 years after entry into HIV care with the highest attrition observed among pregnant women and young PLHIV.
A key finding from our analysis is the enormous increase in access to HIV care and treatment over time. Decentralization efforts have led to greater availability of HIV services at primary health clinics and in rural areas. Previous studies have demonstrated comparable health outcomes among PLHIV who receive care at lower level health facilities and lower rates of lost to follow-up among PLHIV initiating treatment at primary health clinics. [9–11] A study from Malawi found that in one district, expanding access to ART from the district hospital to primary health clinics decreased average travel distance from 7.3 to 4.7 kilometers and led to a 10% increase in visit attendance.  Decentralization has also been accompanied by task shifting, including expansion of nurse initiated ART (NIMART) and development of differentiated care models, such as community ART groups, that are continuing to expand access and make care more patient-oriented. [13–15]
Over the first decade of ART scale-up, women constituted the majority of PLHIV entering care and starting treatment. Our data reflect a dramatic increase in pregnant women initiating ART which could in part be due to improved reporting of pregnancy status at enrollment but mirrors changes in guidelines moving towards Option B+ (ART for all pregnant women).  We also found a high proportion of women enrolling in care who did not return after the first visit and alarmingly high LTF among pregnant women. Overall, 48% of pregnant women were lost before starting treatment and 31% of women who were pregnant at the time of ART initiation were lost to follow-up by 12 months. These data are consistent with previous reports of high loss to follow-up among pregnant women. [17,18] The follow-up period for this analysis ends at the time when many countries were expanding Option B+, however a recent systematic review of retention of pregnant and postpartum women in sub-Saharan Africa in the era of Option B+ by Knettel et al  found that only 76.4% (95%CI 69.0–83.1) were still in care at 12 months after enrollment. These results along with our findings from earlier periods underscore the urgent need to identify strategies to ensure that women remain in care and on treatment through pregnancy, breastfeeding period and thereafter. [20,21]
Perhaps one of the most alarming findings is the large number of patients LTF which is consistent with other studies, including our finding of the highest attrition among pregnant women and younger PLHIV. [8, 22–25] We also report a large proportion (20%) of patients who did not return after their first visit to the health facilities which few other retention analyses have documented. Tracing studies have provided important estimates of outcomes among PLHIV recorded as LTF in routine care settings. In a recent systematic review of outcomes of PLHIV on ART who were lost to follow-up in Africa, it was noted that 34% of patients successfully traced had died and 23.9% had transferred to another health facility, and that over time, in later cohorts, deaths appear to have declined while silent transfer have increased.  In a meta-analysis of data from nine tracing studies, it was noted that among PLHIV LTF after ART initiation, approximately 22% had died, 22% were alive but not on ART, and 15% had transferred to another clinic.  The authors also found that women and PLHIV with less advanced disease at ART initiation were more likely to have undocumented transfers. It is likely that some of the PLHIV identified as LTF in our analysis had undocumented transfer and may still be in care, nonetheless, it is still concerning that close to half of all patients enrolled in HIV care were not retained at three years. It is also possible that the introduction of “treat all” approaches (ART initiation at HIV diagnosis) as recommended by the WHO starting in 2015 will improve attrition; however there are few reports of long-term patient outcomes following the introduction of new guidelines from resource limited settings. While the data used for this analysis are several years old and may not reflect outcomes in the “treat all” era, our findings underscore the urgent need to identify drivers of LTF and to develop differentiated service delivery models that meet the needs and preferences of high-risk PLHIV. [14,15]
Encouragingly, our analysis showed improvement in disease stage among PLHIV at entry to HIV care over time reflecting expanded testing efforts and earlier engagement in care. While we saw fewer clinically advanced patients (WHO stage III/IV) at enrollment and increasing CD4+ counts at both entry and ART initiation, nonetheless, in 2013–2014, 36% of PLHIV enrolling in care across the four countries had CD4+ <200 cells/mm3. PHIA data highlight the continued challenges around early HIV diagnosis; in Tanzania (2016–2017) only 60% of PLHIV were aware of their HIV infection.  Even as attention has shifted toward ‘treat all’ with a focus on immediate ART initiation, it remains critical to identify and provide services targeted to the many PLHIV who continue to enter care and initiate ART with HIV. [27,28]
Strengths of this analysis include the very large sample size, multi-country cohorts, long duration of follow-up, which allowed for three-year retention estimates, and the timespan over the first decade of HIV treatment scale-up. In addition, our data cover the landscape of care settings from tertiary hospitals in urban areas to rural primary health clinics and are from multiple sub-national regions across four countries. These data are highly representative of where most PLHIV receive care in RLS, particularly in sub Saharan Africa, and reflect typical outcomes observed in real world settings. A key weakness is that our data are limited to information recorded in medical charts and are subject to significant amounts of documentation gaps. We also cannot distinguish between gaps in care and missing data, for instance we are unable to determine whether half of all PLHIV enrolled did not have a CD4+ test or whether their results were not recorded in the clinical chart. We also have limited death data drawn only from medical charts.
This analysis of almost one million PLHIV enrolled in HIV care and treatment during a critical decade in the HIV response offers insights from programmatic level supporting the enormous successes of the scale-up of HIV services as well as highlighting the challenges that still remain to be overcome.
S1 Table. National ART guidelines Ethiopia, Kenya, Mozambique, Tanzania and World Health Organization (WHO).
S2 Table. Characteristics at enrollment among adults (> = 15 years) living with HIV enrolled in care at ICAP-supported facilities in Ethiopia, Kenya, Mozambique and Tanzania 2005–2014 by country (N = 884,328).
The authors acknowledge the contributions of the staff and the recipients of care at the participating health facilities, the Ministries of Health in each country and the CDC and PEPFAR for supporting these programs.
- 1. El-Sadr WM, Holmes CB, Mugyenyi P, Thirumurthy H, Ellerbrock T, Ferris R, et al. Scale-up of HIV treatment through PEPFAR: a historic public health achievement. J Acquir Immune Defic Syndr, 2012;60 Suppl 3:S96–104.
- 2. UNAIDS. 2004 Report on the Global AIDS Epidemic. Geneva, Switzerland, 2004. Available at: http://files.unaids.org/en/media/unaids/contentassets/documents/unaidspublication/2004/GAR2004_en.pdf
- 3. UNAIDS. Global HIV & AIDS statistics—2019 fact sheet Geneva, Switzerland: UNAIDS 2019 Available at: https://www.unaids.org/en/resources/fact-sheet.
- 4. Population-based HIV Impact Assessments (PHIA). Available at: https://phia.icap.columbia.edu/.
- 5. Eswatini Go, (CDC) CfDCaP, University IaC. Swaziland HIV Incidence Measurement Survey (SHIMS2) 2016–17: Summary Sheet. Avialable at: https://phia.icap.columbia.edu/wp-content/uploads/2017/11/Swaziland_new.v8.pdf
- 6. Radin E, Birhanu S, Low A, Saito S, Sachatep K, Balachandra S, et al., editors. Late Diagnosis of HIV among Adults in Zimbabwe, Malawi and Zambia: Risk Factors and Burden from Three Population-based HIV Impact Assessments (PHIAs). In: Program and abstractsof the 22nd International AIDS Conference. Amsterdam, The Netherlands, 2018.
- 7. Thin K, Frederix K, McCracken S, Letsie M, Low A, Patel H, et al. Progress toward HIV epidemic control in lesotho: results from a population-based survey. AIDS, 2019;33(15):2393–2401. pmid:31764104
- 8. Zürcher K, Mooser A, Anderegg N, Tymejczyk O, Couvillon MJ, Nash D, et al. IeDEA and MESH consortia. Outcomes of HIV-positive patients lost to follow-up in African treatment programmes. Trop Med Int Health, 2017;22(4):375–387. pmid:28102610
- 9. Reidy W, Agarwal M, Chege D, Lamb M, Hawken M, Mukui I, et al. Retention in Care Among HIV-infected Patients Receiving or Not Receiving Antiretroviral Therapy in Eastern Africa. Clin Infect Dis, 2016;63(3):426–7. pmid:27165659
- 10. Chan AK, Mateyu G, Jahn A, Schouten E, Arora P, Mlotha W, et al. Outcome assessment of decentralization of antiretroviral therapy provision in a rural district of Malawi using an integrated primary care model. Trop Med Int Health, 2010;15 Suppl 1:90–7.
- 11. Bedelu M, Ford N, Hilderbrand K, Reuter H. Implementing antiretroviral therapy in rural communities: the Lusikisiki model of decentralized HIV/AIDS care. J Infect Dis, 2007;196 Suppl 3:S464–8.
- 12. Bilinski A, Birru E, Peckarsky M, Herce M, Kalanga N, Neumann C, et al. Distance to care, enrollment and loss to follow-up of HIV patients during decentralization of antiretroviral therapy in Neno District, Malawi: A retrospective cohort study. PLoS One, 2017;12(10):e0185699. pmid:28973035
- 13. Brennan AT, Long L, Maskew M, Sanne I, Jaffray I, MacPhail P, et al. Outcomes of stable HIV-positive patients down-referred from a doctor-managed antiretroviral therapy clinic to a nurse-managed primary health clinic for monitoring and treatment. AIDS, 2011;25(16):2027–36. pmid:21997488
- 14. Grimsrud A, Bygrave H, Doherty M, Ehrenkranz P, Ellman T, Ferris R, et al. Reimagining HIV service delivery: the role of differentiated care from prevention to suppression. J Int AIDS Soc, 2016;19(1):21484. pmid:27914186
- 15. El-Sadr WM, Rabkin M, DeCock KM. Population health and individualized care in the global AIDS response: synergy or conflict? AIDS, 2016;30(14):2145–8. pmid:27367489
- 16. World Health Organization (WHO). 2013 Consolidated guidelines on the use of antiretroviral drugs for treating and preventing HIV infection. Avaiable at: https://www.who.int/hiv/pub/guidelines/arv2013/en/.
- 17. Wang B, Losina E, Stark R, Munro A, Walensky RP, Wilke M, et al. Loss to follow-up in a community clinic in South Africa—roles of gender, pregnancy and CD4 count. S Afr Med J, 2011;101(4):253–7. pmid:21786730
- 18. Kaplan R, Orrell C, Zwane E, Bekker LG, Wood R. Loss to follow-up and mortality among pregnant women referred to a community clinic for antiretroviral treatment. AIDS, 2008;22(13):1679–81. pmid:18670232
- 19. Knettel BA, Cichowitz C, Ngocho JS, Knippler ET, Chumba LN, Mmbaga BT, et al. Retention in HIV Care During Pregnancy and the Postpartum Period in the Option B+ Era: Systematic Review and Meta-Analysis of Studies in Africa. J Acquir Immune Defic Syndr. 2018. 15;77(5):427–438. pmid:29287029
- 20. Abrams EJ, Langwenya N, Gachuhi A, Zerbe A, Nuwagaba-Biribonwoha H, Mthethwa-Hleta S, et al. Impact of universal antiretroviral therapy for pregnant and postpartum women on antiretroviral therapy uptake and retention. AIDS, 2019;33(1):45–54. pmid:30289804
- 21. Haas AD, Tenthani L, Msukwa MT, Tal K, Jahn A, Gadabu OJ, et al. Retention in care during the first 3 years of antiretroviral therapy for women in Malawi's option B+ programme: an observational cohort study. Lancet HIV, 2016;3(4):e175–82. pmid:27036993
- 22. Chammartin F, Zürcher K, Keiser O, Weigel R, Chu K, Kiragga AN, et al. Outcomes of Patients Lost to Follow-up in African Antiretroviral Therapy Programs: Individual Patient Data Meta-analysis. Clin Infect Dis, 2018;67(11):1643–1652. pmid:29889240
- 23. Fox MP, Rosen S. Retention of Adult Patients on Antiretroviral Therapy in Low- and Middle-Income Countries: Systematic Review and Meta-analysis 2008–2013. J Acquir Immune Defic Syndr, 2015;69(1):98–108. pmid:25942461
- 24. Lamb MR, Fayorsey R, Nuwagaba-Biribonwoha H, Viola V, Mutabazi V, Alwar T, et al. High attrition before and after ART initiation among youth (15–24 years of age) enrolled in HIV care. AIDS, 2014;28(4):559–68. pmid:24076661
- 25. Bygrave H, Mtangirwa J, Ncube K, Ford N, Kranzer K, Munyaradzi D. Antiretroviral therapy outcomes among adolescents and youth in rural Zimbabwe. PloS One, 2012;7(12):e52856. pmid:23285204
- 26. Tanzania HIV Impact Survey (THIS) 2016–17: Summary Sheet. 2018. Available at: https://phia.icap.columbia.edu/wp-content/uploads/2017/11/Tanzania_SummarySheet_A4.English.v19.pdf.
- 27. Teasdale CA, Yuengling K, Preko P, Syowai M, Ndagije F, Rabkin M, et al. Persons living with HIV with advanced HIV disease: Need for novel care models. J Int AIDS Soc. 2018;21(12):e25210. pmid:30549245
- 28. Auld AF, Shiraishi RW, Oboho I, Ross C, Bateganya M, Pelletier V, et al. Trends in Prevalence of Advanced HIV Disease at Antiretroviral Therapy Enrollment—10 Countries, 2004–2015. MMWR Morb Mortal Wkly Rep, 2017;66(21):558–563. pmid:28570507