Skip to main content
NCBI home page
Journal of the International AIDS Society logoLink to Journal of the International AIDS Society
. 2025 Feb 6;28(2):e26415. doi: 10.1002/jia2.26415

Global prevalence of advanced HIV disease in healthcare settings: a rapid review

Nathan Ford 1,2,✉, Reshma Kassanjee 2, Dominik Stelzle 1, Joseph N Jarvis 3,4, Omar Sued 5, Georges Perrin 6, Meg Doherty 1, Ajay Rangaraj 1
PMCID: PMC11802239  PMID: 39915008

Abstract

Introduction

Recent studies have indicated a high enduring burden of advanced HIV disease, but estimates across regions and settings are lacking. The aim of this study was to estimate the prevalence of advanced HIV disease since 2015 among those people with CD4 measured in healthcare settings, disaggregated by age group, level of healthcare and region.

Methods

We searched MedLine via Pubmed and Hinari for studies that reported the proportion of individuals with advanced HIV disease (defined as CD4 cell count <200 cells/mm3) in healthcare settings since 2015; this search was complemented by conference abstracts and data from the International epidemiology Databases to Evaluate AIDS Consortium (IeDEA). We estimated pooled prevalence of advanced HIV disease using random‐effects models and performed subgroup and sensitivity analyses to explore heterogeneity.

Results

We obtained data from 117 cohorts, representing 1,814,362 individuals from 52 countries across all six World Health Organization regions. The majority of studies (n = 83) were conducted among adults and recorded CD4 cell count among treatment naïve individuals at antiretroviral therapy start (n = 86). Studies included data reported up to 2023. The proportion of individuals with advanced HIV disease was higher in inpatient settings (44.3%, 95% CI 39.1−49.6%) compared to outpatient settings (33.5%, 95% CI 31.5−35.4%). Prevalence was similar across age groups, time since HIV diagnosis and treatment status, and highest in West and Central Africa, South‐East Asia and the Eastern Mediterranean region.

Discussion

This review finds that at least a third of people presenting to healthcare settings have advanced HIV disease, with no evidence that this has changed in recent years. Screening for advanced HIV remains important to be able to direct appropriate preventive, diagnostic and therapeutic interventions to prevent progression to severe illness and death.

Conclusions

This review summarizes recent evidence of the continued high proportion of individuals who (re)present to care with advanced HIV disease. These findings underscore the urgent need to reinforce programme capacity to diagnose, prevent and treat advanced HIV disease as an essential pillar of the global AIDS response.

Keywords: advanced HIV disease, CD4 cell count, disengagement, hospital, healthcare setting, severe illness

1. INTRODUCTION

Since 2015, the World Health Organization (WHO) recommended providing antiretroviral therapy (ART) to all people living with HIV irrespective of CD4 cell count. This Treat All recommendation has been adopted as a national policy worldwide, and has reduced HIV transmission and mortality, and increased the life expectancy of individuals living with HIV [1]. Notwithstanding the considerable progress in increasing access to HIV testing and treatment over the last decade, advanced HIV disease remains an important challenge, contributing to a high ongoing burden of severe opportunistic infection, hospitalization and death.

Timely identification of advanced HIV disease with CD4 testing is an important programmatic activity. However, CD4 testing has declined in many low‐ and middle‐income settings since the Treat All recommendation was established, and with this the ability to identify and report the number of individuals with advanced HIV disease. Recent studies from high [2] and low‐income [3] settings that do report CD4 cell count have indicated a high enduring burden of advanced HIV disease. This is in part due to late presentation to care and delayed ART initiation, but increasingly because of individuals cycling out of treatment, returning after a period of treatment interruption [4, 5].

We undertook a rapid review to estimate the prevalence of advanced HIV disease among individuals receiving care in both inpatient and outpatient settings who had a CD4 cell count measurement. This review focused on data published since 2015, the year when the Treat All recommendation was established.

2. METHODS

2.1. Study and data sources

The study was conducted according to PRISMA guidelines following a protocol registered in PROSPERO (CRD42024537211). We screened MedLine via Pubmed and Hinari to search for studies that included the term “advanced HIV disease” (defined as CD4 cell count <200 cells/mm3) in the title or abstract. We also screened abstracts of the International AIDS Society Conference and the Conference on Retroviruses and Opportunistic Infections from 2022 onwards to identify recent studies that have not yet been published in full. We included all studies which reported data between 1st January 2015 (the start of “Treat All”) and 01 March 2024. No language or geographical restrictions were applied. Additional data were includeds from a national HIV programme managers meeting in Thailand in 2024 [6].

We also included country‐level aggregate observational data from HIV treatment programmes provided by the International epidemiology Databases to Evaluate AIDS Consortium (IeDEA) on proportions of persons with CD4 cell count <200 cells/mm3 at ART start at collaborating treatment programmes, stratified by child and adult populations [7]. Reflecting general trends, the proportion of persons in whom CD4 cell count is measured at ART start within IeDEA programmes has declined substantially for countries in sub‐Saharan Africa since 2015: in 2019, over 80% of persons living with HIV in IeDEA programmes in sub‐Saharan Africa (except South Africa) did not have a CD4 test; these estimates, therefore, relate to the small proportions of persons in whom CD4 is measured [8].

2.2. Study inclusion and data extraction

Studies were eligible if they included at least 20 participants within a routine healthcare setting; as such, clinical trials and household surveys were excluded. Studies which spanned periods before and after 01 January 2015 were included if it was possible to disaggregate data from 2015 onwards. We included individuals presenting to care for any reason. Data were disaggregated according to inpatient or outpatient setting, with inpatient settings defined by the studies as a hospital admission. Studies which included a mix of patients were classified according to the majority (>50%) and where such data on the setting were not available, the study was reported as inpatient/outpatient in subgroup analyses. Studies were excluded if they reported exclusively on cohorts of patients living with HIV and other diseases. To assess study quality, we used items of the JBI tool to assess participant recruitment, data completeness, method of data measurement and outcome ascertainment; this information was used to inform the evidence certainty assessment (Supplementary Appendix) [9]. Evidence certainty was assessed using the GRADE framework. For the purposes of this review, we defined a child as aged <15 years.

Data extraction was conducted by one author (NF) and verified by a second author (AR, DS) using a predefined data extraction sheet. If outcomes from the same cohort were published across different publications, each outcome was only reported once.

2.3. Data analysis

We calculated proportions and corresponding 95% confidence intervals (CIs) for the proportion of individuals with advanced HIV disease and pooled data after transformation using random‐effects meta‐analysis [10, 11]. Outcomes of interest were the proportion of patients with advanced HIV disease within a defined cohort. We performed subgroup analyses to assess differences in the proportion of individuals with advanced HIV disease by location (WHO region and income group), age, ART status, new or previous HIV diagnosis and date of data extraction (before or after 2020, to evaluate differences between older and more recent studies). A full linear time‐trend analysis was not possible because individual studies reported data over varying time periods; however, where individual studies provided data across time, this information was highlighted. These pairwise subgroup proportions were limited to outpatient and mixed (i.e. inpatient and outpatient) settings with inpatient studies dropped from these analyses to ensure comparability, and the limited number of inpatient studies prevented separate analyses for this group; subgroups were compared using a two‐sample z‐test for two groups. Statistical tests for heterogeneity do not work well with pooled proportions [12], thus we assessed sources of heterogeneity through visual inspection of forest plot, exploration of outliers and the influence of larger studies on overall estimates [13]. We analysed all data with Stata (version 15.0).

2.4. Role of the funding source

The funder of the study had no role in study design, data interpretation or writing of the report.

3. RESULTS

From an initial screen of 6962 reports, 110 studies were screened as full text and 53 studies were taken through to review (Table 1). An additional 64 study estimates from 38 countries were provided by IeDEA. Together, these 117 studies provided data on 1,814,362 individuals from 53 countries across all WHO regions (Figure 1). The majority of data were from the AFRO region (1,570,490 individuals), including 20 countries (1,547,559 individuals) from eastern and southern Africa and 11 countries (22,931 individuals) from West and Central Africa. Data from 151,155 individuals from 38 countries was contributed by IeDEA. Most studies were conducted among adults (81 studies) and recorded CD4 cell count among individuals at ART start (86 studies). Studies reported data up to 2023, with almost a third (30%, 557,824 individuals) reporting data from 2020 onwards. Fifty‐one cohorts were from outpatient settings, eight from inpatient settings and the remainder (including most IeDEA sites) were from diverse sites. Studies included individuals who were newly diagnosed (28 studies) and those who had been diagnosed previously (42 studies).

Table 1.

Study characteristics

Study Country Date of data extraction Population Newly diagnosed Data source Sample size Number with advanced HIV disease
Afrashteh et al. [14] Iran 2018−2021 Adults No Counselling centre register 249 163
Alli et al. [15] Malawi 2022 NS Yes Hospital records 679 288
Baldeh et al. [16] Sierra Leone 2022−2023 Adults No Hospital records 231 35
Benzekri et al. [17] Senegal 2017−2018 Adults No HIV testing and treatment sites 185 102
Bwalya et al. [18] Zambia 2022 NS No Hospital records 70 30
Chabikuli et al. [19] DRC 2015−2020 Adults, adolescents and children No Health facility data 12,699 5537
Daama et al. [20] Uganda 2021−2022 Adults, adolescents and children Yes Health facility EMR 2254 518
Dat et al. [21] a Vietnam 2015−2017 Adults Yes Outpatient clinical records 3504 1354
Ditondo et al. [22] DRC 2018−2022 Adults No Health facility data 573 288
Elgalib et al. [23] Oman 2015−2019 Adults Yes National HIV surveillance system 603 279
Elizalde‐Barrera and Juarez‐Mendoza [24] Mexico 2015−2021 Adults Yes Newly diagnosed PLHIV referred to care 348 158
Garcia‐Ruiz De Morales et al. [25] Spain 2017−2022 Adults Yes Primary care centres 5200 1185
Gimenez‐Arufe et al. [26] Spain 2015−2020 Adults Yes Newly diagnosed PLHIV, EMR 167 55
Glencross et al. [27] South Africa 2015 Adults No Health facility data 8239 2200
Hamzah et al. [28] UK 2022 Adults Yes Outpatient HIV testing in emergency department 128 53
Heller et al. [29] Malawi 2020 Adults No Medical ward data 460 245
Huang et al. [30] China 2018−2021 Adults Yes Medical records 600 232
Jiang et al. [31] China 2018−2021 Adults Yes National HIV surveillance system 997 400
Kerschberger et al. [32] Eswatini 2016 Adults Yes National ART treatment database 1888 620
Kumar and Singh [33] India 2017 Adults No ART centre records 84 40
Lamp et al. [34] Cameroon, Mozambique, Zimbabwe, Uganda 2016 NS No Routine testing data captured by PIMA analyser 639,658 102,984
Lauscher et al. [2] Germany 2019−2020 Adults Yes Health centre data 706 236
Leeme et al. [3] Botswana 2015−2017 Adults Yes HIV reference laboratory data 14,423 3571
Levy‐Braide et al. [35] Nigeria 2021−2022 NS Yes Facility records 11,781 5487
Li [62] China 2016−2020 Adults Yes Comprehensive Response Information Management System 8575 4027
Lifson et al. [36] Ethiopia 2015−2017 Adults No Records from 16 district hospitals and 16 health centres 1559 942
Mambetov et al. [37] Kyrgyzstan 2020−2021 NS Yes National database 240 79
Masaba et al. [38] Kenya 2016−2019 Adults Yes EMR and paper‐based records 19,427 6649
Mayasi Ngongo et al. [39] DRC 2017−2020 Adults No Monitoring data from 84 health facilities 7908
Mugenyi et al. [40] Uganda 2017−2022 Adults Yes Clinic data 10,446 2151
Musengimana et al. [41] Rwanda 2016−2018 Adults No EMR 957 105
Mwakisambwe et al. [42] Tanzania 2020−2021 Adults Yes Routine healthcare data 70,302 13,994
Nalintya et al. [43] Uganda 2019−2022 NS No Routine clinic data 39,903 6171
Ndlovu et al. [44] Malawi, Zimbabwe, DRC 2017 Adults No Clinic data 708 221
Nhampossa et al. [45] Mozambique 2015−2020 Adults No Clinic data 2458 349
Noknoy [6] Thailand 2015−2022 Adults, adolescents and children No Clinic data 149,521 50,673
Oboho et al. [46] Uganda, Kenya, Tanzania, Nigeria 2015−2021 Adults No Clinic data 23,288 1919
Osler et al. [4] South Africa 2015−2017 Adults No Data linkage between lab reported CD4 and HIV treatment information systems 557,566 116,234
Otani et al. [47] Japan 2015−2019 Adults Yes >100 collaborating institutions of a drug resistance HIV surveillance network 2533 1141
Ousley et al. [48] Kenya and DRC 2015−2017 Adults No Clinic data 707 460
Owachi et al. [49] Uganda 2020−2023 Adults No Hospital data 5827 2271
Parisi et al. [50] USA 2015−2021 Adults Yes Enhanced HIV/AIDS Reporting System 27,460 6316
Pedrola et al. [51] Argentina 2022 Adults, adolescents and children Yes Database of 35 testing centres 620 129
Raberahona et al. [52] Madagascar 2015−2016 Adults Yes Inpatient and outpatient medical records 150 90
Samayoa et al. [53] Guatemala 2017 Adults Yes 13 HIV clinics 1323 630
Shi et al. [54] China 2015−2020 Adults Yes Provincial surveillance system 20,791 14,572
Spinelli et al. [55] USA 2021 Adults No Clinic data 1816 272
Ssempijja et al. [56] Uganda 2018−2020 Adults No 187 48
Stoger et al. [57] Tanzania 2016−2019 Adults Yes Clinic data 1046 583
Subramanian et al. [58] India 2022 Adults — Clinic data 1504 255
Dagnaw Tegegne et al. [59] Ethiopia 2015−2020 Adults No Hospital data 354 115
Tiam et al. [60] Lesotho 2018−2019 Adults No Clinic data 150 70
Yendewa et al. [61] Sierra Leone 2017 Adults Yes Hospital data 155 76
Open in a new tab

Abbreviations: EMR, electronic medical record; NS, not stated; PLHIV, people living with HIV.

a

Study limited to individuals with CD4 <100.

Figure 1.

Figure 1

Open in a new tab

Study selection process.

Overall, studies were rated as being at moderate risk of bias (Supplementary Appendix), with considerable heterogeneity in outcomes, as expected considering differences in healthcare setting, national HIV epidemic and programmatic response. The certainty of the evidence was rated as low due to concerns related to risk of bias (representativeness of the study population and retrospective data collection), and imprecision and inconsistency in the subgroup estimates (notably setting and region).

The pooled proportion of advanced HIV disease was higher in inpatient settings (44.3%, 95% CI 39.1−49.6%) compared to outpatient settings (33.5%, 95% CI 31.5−35.4%) (Figure 2). Two studies reported data stratified by healthcare setting: the first study used data from a provincial surveillance system in China and found a higher prevalence of advanced HIV disease among inpatients (42.1%, 41.2−43.0%) compared to outpatients (20.3%, 19.8−20.9%) [54]; the second study, using data from a tertiary hospital in Sierra Leone, found a higher prevalence of advanced HIV disease among inpatients (51.5%, 39.0−63.8) compared to outpatients (39.3%, 31.7−47.2), but this difference was not significant (p = 0.1).

Figure 2.

Figure 2

Open in a new tab

Summary estimates of advanced HIV disease prevalence in health care settings. AHD, advanced HIV disease. Studies that reported data from both inpatient and outpatient settings not included.

In prespecified subgroup analyses for outpatient and mixed settings, overall estimates were similar across age groups, comparing studies limited to ART naïve individuals and studies in which the majority of participants (>50%) reported taking ART, and time since HIV diagnosis (newly diagnosed vs. previously diagnosed). Prevalence was similar comparing studies that only included data from 2020 onwards (31.0%, 95% CI 17.6−44.1%) and studies reporting data from 2015 to 2019 (34.0%, 95% CI 31.9−36.1%), consistent with studies which reported data over time [3, 6, 23, 26, 34, 54, 62]. Prevalence was highest in West and Central Africa, South‐East Asia, the America and the eastern Mediterranean region (Figure 3). There was no difference by country economic grouping.

Figure 3.

Figure 3

Open in a new tab

Subgroup analyses. AHD, advanced HIV disease; ART, antiretroviral therapy. All analyses other than setting restricted to outpatient and mixed settings (inpatient studies dropped from analysis).

In a sensitivity analysis assessing the possible influence of larger studies, the overall estimate did not change importantly if the three largest studies (each with n>100,000) [4, 6, 34] or if data from IeDEA were excluded from the analysis (both p = 0.8).

Seven studies provided near complete datasets for CD4 cell counts for a given region: a national surveillance system of Oman [23], electronic medical records for a health catchment area in Spain [26], a centralized database of all CD4 measures transmitted via the Alere Pima Analyzer in Cameroon, Mozambique, Uganda and Zimbabwe [34], a central reference laboratory processing nearly all CD4 measures in Gaborone, Botswana [3], a case reporting system in southwest China [62], a provincial dataset from eastern China [54] and a national surveillance system in Thailand [6]; a number of these studies provide estimates of trends over time [6, 24, 26, 34, 54, 62]. No difference was found comparing prevalence estimates derived from these datasets and the other studies in these regions.

4. DISCUSSION

This review provides further evidence that, despite good progress towards meeting the 95‐95‐95 global targets and improved access to diagnosis and ART, advanced HIV disease remains an important challenge across age groups. We found that around a third of individuals initiating ART in healthcare settings and in whom CD4 is measured have advanced HIV disease, with a higher proportion among PLHIV admitted to hospital.

These findings confirm the importance of maintaining a focus on reducing HIV‐associated illness and death as a core component of the global AIDS response. An essential first step is to ensure that programmes can and do screen correctly for advanced HIV disease among the following: individuals who present to care; those who re‐present after a period of disengagement; those found to have non‐suppressed viral loads on routine monitoring; and those who become unwell. CD4 testing, the preferred tool to diagnose advanced HIV disease, has declined to very low levels in many resource‐limited settings, particularly in sub‐Saharan Africa, and this partly explains the lack of data for a number of countries and population groups [63]. The decline in CD4 testing capacity has been linked to budget limitations, forcing programmes to prioritize viral load monitoring. A decrease in demand has resulted in reduced supply, with several manufacturers opting to withdraw their tests from the market [64]. Where CD4 count testing is unavailable, clinical staging is used to diagnose advanced HIV disease; however, staging has poor diagnostic accuracy, meaning that an important number of individuals who could benefit from interventions to reduce disease progression and mortality would be missed [65].

Until recently, advanced HIV disease was considered a challenge associated with late diagnosis and presentation to care at an advanced stage of illness [66]. As ART coverage has increased, there is a growing appreciation that a substantial number of people with advanced HIV disease are individuals who had started ART but subsequently disengaged from care, returning when they are ill [4]. This review further strengthens this finding that advanced HIV disease is common among both newly diagnosed, ART naïve individuals, and individuals who were previously diagnosed and have received treatment. Despite notable improvements in ART coverage during the time period chosen for this review, the relative estimated proportions of advanced HIV disease do not appear to have declined significantly. For studies that reported data across several years, no relationship was found between increased national ART coverage and advanced HIV disease prevalence [6, 24, 54]. For example, ART coverage in Thailand increased from 67% to 90%, but the proportion of individuals with advanced HIV disease remained constant throughout this period [6, 67]. There was insufficient data to explore the contribution made by disengagement in care, and this remains an important research question.

Access to healthcare services was disrupted during the COVID‐19 pandemic, leading to a decreased ability to detect and treat advanced HIV disease during this period. This was reported by several studies included in this review which compared the proportion of patients presenting with advanced HIV disease before and during the COVID‐19 pandemic. A study from Malawi found that hospital admissions halved in 2020 compared to historical data from 2017, attributing this change to difficulties in reaching healthcare facilities due to lockdown and fear of COVID‐19 infection [29]. Another study, from Uganda, reported that only 9% of people living with HIV presented with advanced HIV disease during COVID‐19 lockdowns (March−July 2020) compared to 16% during the period between July 2019 and February 2020 [43].

A recent study assessed the proportion of individuals with advanced HIV disease using data from population‐based HIV impact assessment household surveys and reported a prevalence of 10%, notably lower than the figure provided in this review [68]. This difference is explained by the fact that this review focused on individuals presenting to healthcare settings for whom a CD4 count was done and so more likely to have advanced HIV disease. This underscores the importance of considering setting when reporting estimates of advanced HIV disease.

4.1. Limitations of the available evidence

This review identified studies from a range of settings across all WHO regions and different economic areas, and included both published and unpublished data. The available evidence has several limitations. The majority of studies were from the African region, reflecting the global burden of HIV. There was little data from other regions, notably the eastern Mediterranean and Latin America, and few studies were identified among children; this highlights the need for data from a broader set of patient populations and countries. All children younger than 5 years are defined as having advanced disease except for those receiving ART for more than 1 year and who are clinically stable [69]; as such, the proportion of children with advanced HIV disease is likely to be higher than reported in this review. There were also fewer studies reporting data from inpatient settings.

It should also be emphasized that even among the included studies, data on CD4 cell count was for the most part limited: only a sub‐population of (possibly non‐random) people living with HIV who had a CD4 measured contributed data. For example, in IeDEA programmes, CD4 testing has become extremely limited in many settings [63], and people who do get a CD4 measurement may have higher levels of severe immune suppression compared to all people living with HIV starting ART in the country. Another limitation to note is that meta‐analyses of aggregate data are prone to ecological bias, and trends in CD4 cell count changes would be more reliably assessed using individual‐level data [70].

4.2. Limitations of the review methodology

This review used standard systematic review search methods, including multiple database and conference abstract screening; this information was further supported by data provided by IeDEA and from the national programme of Thailand. An important limitation of this review is the limited search strategy, including restricted search terms and limited database searches—this is why we choose to characterize this study conservatively as a rapid review. Studies that reported on the proportion of individuals with a CD4 <200 cells/mm3 but did not use the term advanced HIV disease, would not have been captured by this review. The use of such a focused search strategy was a pragmatic choice based on available resources, and the review was identified as a rapid review to indicate this limitation. We complemented this search through the inclusion of conference abstracts and unpublished data, including data provided by the IeDEA consortium, and national programme data. The identification of additional studies could strengthen some of the subgroup estimates where the available data was limited, in particular for children and for a number of countries. Nevertheless, the overall estimate was consistent across a number of subgroups and additional studies would be unlikely to change this estimate importantly.

5. CONCLUSIONS

This review provides further evidence of the continued high proportion of individuals who (re)present to care with advanced HIV disease. Future research should be directed to supporting a better understanding of reasons for both late diagnosis and disengagement in care as key drivers sustaining the high burden of advanced HIV disease. There is also a need for more research to better determine the outcomes of people diagnosed with advanced HIV disease, including the effectiveness of interventions to prevent, diagnose and treat opportunistic infections, and causes of severe disease, hospitalization and mortality. Diagnosing individuals with advanced HIV remains an important challenge to overcome, to be able to direct appropriate preventive, diagnostic and therapeutic interventions to prevent progression to severe illness and death. CD4 testing thus remains an essential tool in the programmatic response to advanced HIV disease.

COMPETING INTERESTS

The authors declare no competing interests.

AUTHORS’ CONTRIBUTIONS

Conceptualization: NF, DS and JJ. Data curation: NF, RK, DS and AR. Formal analysis: NF. Methodology: NF, RK, DS and JJ. Project administration: NF. Software: NF. Supervision: NF and AJ. Validation: NF and DS. Visualization: NF. Writing original draft: NF. Writing—review and editing: NF, RK, DS, JJ, OS, GP, MD and AR.

FUNDING

This work was supported by a grant from the Gates Foundation (INV‐070‐0909) The International Epidemiology Databases to Evaluate AIDS (IeDEA) is supported by the U.S. National Institutes of Health's National Institute of Allergy and Infectious Diseases, the Eunice Kennedy Shriver National Institute of Child Health and Human Development, the National Cancer Institute, the National Institute of Mental Health, the National Institute on Drug Abuse, the National Heart, Lung, and Blood Institute, the National Institute on Alcohol Abuse and Alcoholism, the National Institute of Diabetes and Digestive and Kidney Diseases, and the Fogarty International Center: Asia‐Pacific, U01AI069907; CCASAnet, U01AI069923; Central Africa, U01AI096299; East Africa, U01AI069911; NA‐ACCORD, U01AI069918; Southern Africa, U01AI069924; West Africa, U01AI069919. Informatics resources are supported by the Harmonist project, R24AI24872.

DISCLAIMER

This work is solely the responsibility of the authors and does not necessarily represent the official views of any of the institutions mentioned above.

Supporting information

Supporting Information

JIA2-28-e26415-s001.docx (29.4KB, docx)

ACKNOWLEDGEMENTS

We would like to thank Mohammad Fararouei and Zibusiso Ndlovu for data clarifications on their published studies.

DATA AVAILABILITY STATEMENT

The data that support the findings of this study are openly available in the published articles included in this review and summarized in Table 1. Data from IeDEA are available upon reasonable request. Investigators wishing to work with IeDEA data should contact the regional data centres (see www.iedea.org) and submit a concept sheet for their intended analysis and data request.

REFERENCES

  • 1. Ghosn J, Taiwo B, Seedat S, Autran B, Katlama C. HIV. Lancet. 2018;392(10148):685–97. [DOI] [PubMed] [Google Scholar]
  • 2. Lauscher P, Hanhoff N, Valbert F, Schewe K, Koegl C, Bickel M, et al. Socio‐demographic and psycho‐social determinants of HIV late presentation in Germany ‐ results from the FindHIV study. AIDS Care. 2023;35(11):1749–59. [DOI] [PubMed] [Google Scholar]
  • 3. Leeme TB, Mine M, Lechiile K, Mulenga F, Mosepele M, Mphoyakgosi T, et al. Utility of CD4 count measurement in the era of universal antiretroviral therapy: an analysis of routine laboratory data in Botswana. HIV Med. 2021;22(1):1–10. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4. Osler M, Hilderbrand K, Goemaere E, Ford N, Smith M, Meintjes G, et al. The continuing burden of advanced HIV disease over 10 years of increasing antiretroviral therapy coverage in South Africa. Clin Infect Dis. 2018;66(suppl_2):S118‐S25. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5. Burke RM, Rickman HM, Pinto C, Ehrenkranz P, Choko A, Ford N. Reasons for disengagement from antiretroviral care in the era of “Treat All” in low‐ or middle‐income countries: a systematic review. J Int AIDS Soc. 2024;27(3):e26230. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6. Noknoy S. Experience in providing AHD package for PLHIV, slide presentation National Programme Managers’ Meeting on Strengthening Implementation of Integrated Service Delivery to End AIDS, Viral Hepatitis and STIs in the South‐East Asia Region . 2024.
  • 7. https://www.iedea.org/ Accessed 22 January 2025.
  • 8. de Waal R, Wools‐Kaloustian K, Brazier E, Althoff KN, Jaquet A, Duda SN, et al. Global trends in CD4 count measurement and distribution at first antiretroviral treatment initiation. Clin Infect Dis. 2024:ciae548. Online ahead of print [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9. Migliavaca CB, Stein C, Colpani V, Munn Z, Falavigna M; Prevalence Estimates Reviews ‐ Systematic Review Methodology Group . Quality assessment of prevalence studies: a systematic review. J Clin Epidemiol. 2020;127:59–68. [DOI] [PubMed] [Google Scholar]
  • 10. Freeman MF, Tukey JW. Transformations related to the angular and the square root. Ann Math Stat. 1950;21:607–611. [Google Scholar]
  • 11. Miller J. The inverse of the Freeman−Tukey double arcsine transformation. Am Stat. 1978;32:138. [Google Scholar]
  • 12. Mills EJ, Jansen JP, Kanters S. Heterogeneity in meta‐analysis of FDG‐PET studies to diagnose lung cancer. JAMA. 2015;313(4):419. [DOI] [PubMed] [Google Scholar]
  • 13. Viechtbauer W, Cheung MW. Outlier and influence diagnostics for meta‐analysis. Res Synth Methods. 2010;1(2):112–25. [DOI] [PubMed] [Google Scholar]
  • 14. Afrashteh S, Fararouei M, Ghaem H, Aryaie M. Factors associated with baseline CD4 cell counts and advanced HIV disease among male and female HIV‐positive patients in Iran: a retrospective cohort study. J Trop Med. 2022;2022:8423347. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15. Alli H, Kanyola C, Chione B, Msambula, Kachepa G, Kiruthu‐Kamamia C, et al. Bringing it closer to the recipients of care: the effectiveness of point of care hospital inpatient services at Queen Elizabeth Central Hospital, Malawi. IAS. 2023. Abstract EPE0919.
  • 16. Baldeh M, Kizito S, Lakoh S, Sesay D, Dennis F, Barrie U, et al. Prevalence and factors associated with advanced HIV disease among young people aged 15–24 years in a national referral hospital in Sierra Leone: a cross‐sectional study. medRxiv. 2023. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17. Benzekri NA, Sambou JF, Ndong S, Tamba IT, Faye D, Diallo MB, et al. Prevalence, predictors, and management of advanced HIV disease among individuals initiating ART in Senegal, West Africa. BMC Infect Dis. 2019;19(1):261. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18. Bwalya C, Muchanga G, Hachaambwa L, Musinda T, Mwale M, Daka T, et al. Inpatient navigation model to improve delivery of advanced HIV disease package for hospitalized adults with HIV in Zambia: a randomized pilot trial. IAS 2023. Abstract EPE0955.
  • 19. Chabikuli ON, Ditekemena JD, Sigwadhi LN, Mulenga A, Mboyo A, Bidashimwa D, et al. Advanced HIV disease at antiretroviral therapy initiation and treatment outcomes among children and adolescents compared to adults living with HIV in Kinshasa, Democratic Republic of the Congo. J Int Assoc Provid AIDS Care. 2023;22. 1‐10 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20. Daama A, Nalugoda F, Kasango A, Nantume B, Kigoze G, SSekubugu R, et al. Prevalence and predictors of advanced disease among people living with HIV in Masaka Region, Uganda. CROI 2024. Abstract 1186. [Google Scholar]
  • 21. Dat VQ, Lyss S, Dung NTH, Hung LM, Pals SL, Anh HTV, et al. Prevalence of advanced HIV disease, cryptococcal antigenemia, and suboptimal clinical outcomes among those enrolled in care in Vietnam. J Acquir Immune Defic Syndr. 2021;88(5):487–96. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22. Ditondo P, Luemba A, Chuy RI, Mucinya G, Ade S. Contribution des diagnopstics au points de service dans l'identification de la maladie à VIH avancée . Public Health Action. 2023;13(2 Suppl 1):7–12. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23. Elgalib A, Shah S, Al‐Wahaibi A, Al‐Habsi Z, Al‐Fouri M, Lau R, et al. Predictors of late presentation and advanced HIV disease among people living with HIV in Oman (2000–2019). BMC Public Health. 2021;21(1):2029. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24. Elizalde‐Barrera CI, Juarez‐Mendoza CV. Late diagnosis at entry on care in an HIV clinic in Mexico City: possibly COVID‐19 pandemic impact. Curr HIV Res. 2023;21(4):248–53. [DOI] [PubMed] [Google Scholar]
  • 25. Garcia‐Ruiz De Morales A, Martinez‐Sanz J, Vivancos M, Romero Hernandez B, Montero Alonso M, Valls M, et al. Late HIV diagnosis in CoRIS, 2012–2022, and impact of a formative session in 20 primary care centers. CROI 2024. Abstract 1081. [Google Scholar]
  • 26. Gimenez‐Arufe V, Rotea‐Salvo S, Martinez‐Pradeda A, Mena‐de‐Cea Á, Margusino‐Framiñán L, Suanzes‐Hernández J, et al. Analysing early diagnosis strategies for HIV infection: a retrospective study of missed diagnostic opportunities. Healthcare (Basel). 2024;12(3):361. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27. Glencross DK, Cassim N, Coetzee LM. Documented higher burden of advanced and very advanced HIV disease among patients, especially men, accessing healthcare in a rapidly growing economic and industrial hub in South Africa: a call to action. S Afr Med J. 2020;110(6):505–13. [DOI] [PubMed] [Google Scholar]
  • 28. Hamzah L, Childs K, Cormack I, Davies O, Font R, Haddow L, et al. Opt‐out HIV testing in emergency departments successfully addresses key gaps in testing. CROI 2024. Abstract 205. [Google Scholar]
  • 29. Heller T, Damba D, Kumwenda T, Huwa J, Kamamia C, Nhlema A, et al. Implementing advanced HIV disease care for inpatients in a referral hospital in Malawi – demand, results and cost implications. Ann Glob Health. 2022;88(1):16. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30. Huang Y, Yang C, Lee Y .. Similar short‐term outcomes with same‐day ART initiation vs rapid ART initiation. CROI 2022. Abstract 902. [Google Scholar]
  • 31. Jiang H, Liu J, Tan Z, Fu X, Xie Y, Lin K, et al. Prevalence of and factors associated with advanced HIV disease among newly diagnosed people living with HIV in Guangdong Province, China. J Int AIDS Soc. 2020;23(11):e25642. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32. Kerschberger B, Schomaker M, Jobanputra K, Kabore SM, Teck R, Mabhena E, et al. HIV programmatic outcomes following implementation of the ‘Treat‐All’ policy in a public sector setting in Eswatini: a prospective cohort study. J Int AIDS Soc. 2020;23(3):e25458. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33. Kumar V, Singh J. A prospective study on impact of early initiation of antiretroviral therapy in human immunodeficiency virus‐positive adults on immunological status and adverse events. J Glob Infect Dis. 2019;11(2):73–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34. Lamp K, McGovern S, Fong Y, Atem CD, Nfetam JBE, Nzuobontane D, et al. Proportions of CD4 test results indicating advanced HIV disease remain consistently high at primary health care facilities across four high HIV burden countries. PLoS One. 2020;15(1):e0226987. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35. Levy‐Braide B, Otubu N, Abudiore O, Eigege W, Sowale O, Inyang A, et al. Lessons learned from the introduction of advanced HIV disease package of care in Nigeria. CROI 2024. Abstract 196; IAS 2023. Abstract MOPEE21. [Google Scholar]
  • 36. Lifson AR, Workneh S, Hailemichael A, MacLehose RF, Horvath KJ, Hilk R, et al. Advanced HIV disease among males and females initiating HIV care in rural Ethiopia. J Int Assoc Provid AIDS Care. 2019;18. 1‐7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37. Mambetov T, Cassell M, Fischer Walker C, Gottlieb A, Samoylova O, Saliev D, et al. Identifying the differentiating characteristics of HIV treatment clients with advanced HIV disease in Kyrgyzstan. IAS 2023. Abstract EPD0568. [Google Scholar]
  • 38. Masaba RO, Herrera N, Siamba S, Ouma M, Okal C, Mayi A, et al. Advanced HIV disease in Homa Bay County, Kenya: characteristics of newly‐diagnosed and antiretroviral therapy‐experienced clients. Medicine (Baltimore). 2023;102(51):e36716. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39. Mayasi Ngongo N, Kamangu Ntambwe E, Situakibanza Nani‐Tuma H, Mbula Mambimbi M, Mandina Ndona M, Longokolo Mashi M, et al. Human immunodeficiency virus viral load monitoring and rate of virologic suppression among patients receiving antiretroviral therapy in Democratic Republic of the Congo, 2013–2020. Open Forum Infect Dis. 2023;10(6):ofad242. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40. Mugenyi L, Hansen CH, Mayaud P, Seeley J, Newton R, Nanfuka M, et al. Effect of the “universal test and treat” policy on the characteristics of persons registering for HIV care and initiating antiretroviral therapy in Uganda. Front Public Health. 2023;11:1187274. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41. Musengimana G, Umugisha JP, Habinshuti P, Anderson T, Mukesharurema G, Remera E, et al. Characteristics and clinical outcomes of patients presenting with advanced HIV disease in the “treat all” era: a retrospective cohort study from rural Rwanda. BMC Infect Dis. 2022;22(1):706. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42. Mwakisambwe J, Kiravu A, Masini A, Chisonjela F, Kaduma A, Samatta T, et al. Magnitude of opportunistic infections among people diagnosed with advanced HIV disease in routine healthcare and their one‐year outcomes in Tanzania. IAS 2023. Abstract EPE0132. [Google Scholar]
  • 43. Nalintya E, Sekar P, Kavuma P, Kigozi J, Ssuna M, Kirumira P, et al. Effect of coronavirus disease 2019 lockdowns on identification of advanced human immunodeficiency virus disease in outpatient clinics in Uganda. Clin Infect Dis. 2023;76(11):2014–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44. Ndlovu Z, Massaquoi L, Bangwen NE, Batumba JN, Bora RU, Mbuaya J, et al. Diagnostic performance and usability of the VISITECT CD4 semi‐quantitative test for advanced HIV disease screening. PLoS One. 2020;15(4):e0230453. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45. Nhampossa T, Gonzalez R, Nhacolo A, Garcia‐Otero L, Quintó L, Mazuze M, et al. Burden, clinical presentation and risk factors of advanced HIV disease in pregnant Mozambican women. BMC Pregnancy Childbirth. 2022;22(1):756. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46. Oboho IK, Esber AL, Dear N, Paulin HN, Iroezindu M, Bahemana E, et al. Advanced HIV disease in East Africa and Nigeria, in The African Cohort Study. J Acquir Immune Defic Syndr. 2024;96(1):51–60. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47. Otani M, Shiino T, Hachiya A, Gatanaga H, Watanabe D, Minami R, et al. Association of demographics, HCV co‐infection, HIV‐1 subtypes and genetic clustering with late HIV diagnosis: a retrospective analysis from the Japanese Drug Resistance HIV‐1 Surveillance Network. J Int AIDS Soc. 2023;26(5):e26086. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48. Ousley J, Niyibizi AA, Wanjala S, Vandenbulcke A, Kirubi B, Omwoyo W, et al. High proportions of patients with advanced HIV are antiretroviral therapy experienced: hospitalization outcomes from 2 sub‐Saharan African sites. Clin Infect Dis. 2018;66(suppl_2):S126‐S31. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 49. Owachi D, Akatukunda P, Nanyanzi DS, Katwesigye R, Wanyina S, Muddu M, et al. Mortality and associated factors among people living with HIV admitted at a tertiary‐care hospital in Uganda: a cross‐sectional study. BMC Infect Dis. 2024;24(1):239. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50. Parisi C, Cook R, Li Z, Canidate SS, Kwara A, Zhou Z, et al. Rethinking the definition of late HIV diagnosis using Florida Surveillance Data, 2015–2021. CROI 2024. Abstract 1043 [Google Scholar]
  • 51. Pedrola M, Haag N, Alaniz G, Bagilet F. New challenges to optimize early diagnosis of HIV infection in the post‐COVID‐19 pandemic. IAS 2023. Abstract EPC0455. [Google Scholar]
  • 52. Raberahona M, Rakotomalala R, Andriananja V, Andriamamonjisoa J, Rakotomijoro E, Andrianasolo RL, et al. A retrospective cohort analysis of people living with HIV/AIDS enrolled in HIV care at a reference center in Antananarivo, Madagascar. Front Public Health. 2023;11:1329194. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 53. Samayoa B, Aguirre L, Bonilla O, Medina N, Lau‐Bonilla D, Mercado D, et al. The diagnostic laboratory hub: a new health care system reveals the incidence and mortality of tuberculosis, histoplasmosis, and cryptococcosis of PWH in Guatemala. Open Forum Infect Dis. 2020;7(1):ofz534. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 54. Shi L, Tang W, Liu X, Hu H, Qiu T, Chen Y, et al. Trends of late HIV presentation and advance HIV disease among newly diagnosed HIV cases in Jiangsu, China: a serial cross‐sectional study from 2008 to 2020. Front Public Health. 2022;10:1054765. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 55. Spinelli M, LeTourneau N, Glidden D, Hsu L, Hickey M, Imbert E, et al. Increased HIV viral suppression during Covid‐19 among US urban people with HIV. CROI 2022. Abstract 888. [Google Scholar]
  • 56. Ssempijja V, Callier V, Nason M, Anok A, Lisco A, Redd A, et al. Herpes viruses reactivation and associated systemic inflammation during initiating ART, Rakai‐Uganda. CROI. 2024. Abstract 322. [Google Scholar]
  • 57. Stoger L, Katende A, Mapesi H, Kalinjuma AV, van Essen L, Klimkait T, et al. Persistent high burden and mortality associated with advanced HIV disease in rural Tanzania despite uptake of World Health Organization “test and treat” guidelines. Open Forum Infect Dis. 2022;9(12):ofac611. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 58. Subramanian A, Dixit A, Bansal Y, Kataria S, Rathakrishnan D, Moore A, et al. Lessons learned from pilot implementation of cryptococcal meningitis (CM) care package for people with advanced HIV (AHD) in Delhi, India. IAS. 2023. Abstract EPE0841. [Google Scholar]
  • 59. Dagnaw Tegegne K, Cherie N, Tadesse F, Tilahun L, Kassaw MW, Biset G. Incidence and predictors of opportunistic infections among adult HIV infected patients on anti‐retroviral therapy at Dessie comprehensive specialized hospital, Ethiopia: a retrospective follow‐up study. HIV AIDS (Auckl). 2022;14:195–206. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 60. Tiam A, Paulin H, Machekano R, Oboho I, Agyemang E, Mugyenyi FA, et al. Rapid antiretroviral therapy initiation in patients with advanced HIV disease: 6‐month outcomes of an observational cohort evaluation in Lesotho. PLoS One. 2023;18(10):e0292660. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 61. Yendewa GA, Poveda E, Lakoh S, Yendewa SA, Jiba DF, Salgado‐Barreira A, et al. High prevalence of late‐stage disease in newly diagnosed human immunodeficiency virus patients in Sierra Leone. Open Forum Infect Dis. 2018;5(9):ofy208. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 62. Li SS, Li K, Chen HH, Zhu QY, He JS, Feng Y, et al. Evaluation of factors associated with high advanced HIV disease and mortality in Southwestern China: a retrospective cohort study, 2005–2020. Public Health. 2024;227:282–90. [DOI] [PubMed] [Google Scholar]
  • 63. De Waal R, Wools‐Kaloustian K, Brazier E, Althoff KN, Jacquet A, Duda S, et al. Global trends in CD4 count measurement and prevalence of CD4. CROI 2024. Abstract 1046. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 64. Syarif O, Oladele R, Gils T, Rajasingham R, Falconer J, Achii P, et al. Resolving the CD4‐testing crisis to help end AIDS‐related deaths. Lancet Glob Health. 2025;13(1):e16‐e18. [DOI] [PubMed] [Google Scholar]
  • 65. Munthali C, Taegtmeyer M, Garner PG, Lalloo DG, Squire SB, Corbett EL, et al. Diagnostic accuracy of the WHO clinical staging system for defining eligibility for ART in sub‐Saharan Africa: a systematic review and meta‐analysis. J Int AIDS Soc. 2014;17(1):18932. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 66. Montlahuc C, Guiguet M, Abgrall S, Daneluzzi V, de Salvador F, Launay O, et al. Impact of late presentation on the risk of death among HIV‐infected people in France (2003–2009). J Acquir Immune Defic Syndr. 2013;64(2):197–203. [DOI] [PubMed] [Google Scholar]
  • 67. https://www.unaids.org. Accessed 22 January 2025.
  • 68. Stelzle D, Rangaraj A, Jarvis J, Razakasoa NH, Low‐Beer D, Doherty M, et al. High prevalence of advanced HIV disease in sub‐Saharan Africa: an analysis of 11 household surveys. CROI 2024. Abstract 196. [Google Scholar]
  • 69. WHO C, EGPAF, UNITAID . Package of care for children and adolescents with advanced HIV disease: STOP AIDS. Technical brief. 2020.
  • 70. Ford N, Mills EJ, Egger M. Editorial commentary: Immunodeficiency at start of antiretroviral therapy: the persistent problem of late presentation to care. Clin Infect Dis. 2015;60(7):1128–30. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supporting Information

JIA2-28-e26415-s001.docx (29.4KB, docx)

Data Availability Statement

The data that support the findings of this study are openly available in the published articles included in this review and summarized in Table 1. Data from IeDEA are available upon reasonable request. Investigators wishing to work with IeDEA data should contact the regional data centres (see www.iedea.org) and submit a concept sheet for their intended analysis and data request.

Articles from Journal of the International AIDS Society are provided here courtesy of Wiley

RESOURCES