About the Author(s)


Lindokuhle Ndlazi Email symbol
Department of Public Health, School of Healthcare Sciences, Sefako Makgatho Health Sciences University, Tshwane, South Africa

Mathildah M. Mokgatle symbol
Department of Public Health, School of Healthcare Sciences, Sefako Makgatho Health Sciences University, Tshwane, South Africa

Lindiwe P. Cele symbol
Department of Public Health, School of Healthcare Sciences, Sefako Makgatho Health Sciences University, Tshwane, South Africa

Raikane J. Seretlo symbol
Department of Public Health, School of Healthcare Sciences, Sefako Makgatho Health Sciences University, Tshwane, South Africa

Citation


Ndlazi L, Mokgatle MM, Cele LP, Seretlo RJ. Prevalence and factors associated with HIV viral rebound in individuals on ART: A systematic review study. J Public Health Africa. 2025;16(1), a1324. https://doi.org/10.4102/jphia.v16i1.1324

Review Article

Prevalence and factors associated with HIV viral rebound in individuals on ART: A systematic review study

Lindokuhle Ndlazi, Mathildah M. Mokgatle, Lindiwe P. Cele, Raikane J. Seretlo

Received: 13 Feb. 2025; Accepted: 02 May 2025; Published: 15 Aug. 2025

Copyright: © 2025. The Author(s). Licensee: AOSIS.
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 work is properly cited.

Abstract

Background: Viral rebound (VR), the resurgence of detectable human immunodeficiency virus (HIV) viral loads (> 50 copies/mL) after suppression, remains a challenge for individuals on antiretroviral therapy (ART) in South Africa, despite free access to treatment.

Aim: This systematic review aimed to determine the prevalence of HIV VR and its contributing factors among individuals on ART.

Setting: This is a systematic review study, it relies primarily on secondary data, and it does not have a physical setting.

Method: This study is conducted in line with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and the Cochrane methodology, and the study was registered with PROSPERO (ID: CRD42024524121). Data were sourced from PubMed, EBSCOhost and Scopus, yielding 89 684 articles. After screening in Rayyan, 23 articles met the inclusion criteria. The risk of bias was assessed using the Joanna Briggs Institute’s (JBI’s) appraisal tool.

Results: Viral rebound varies across different populations. Contributing factors included biological, genetic, demographic, socio-economic and structural elements, as well as incarceration, missed appointments, lifestyle behaviours, travel, multiple sexual partners, ART regimen, age and clinical management. Poor ART adherence emerged as a key driver.

Conclusion: Human immunodeficiency virus viral rebound results from a combination of biological, social and treatment-related factors, with non-adherence to ART being a major contributor. The study highlights the need for improved adherence strategies to reduce VR.

Contribution: This review enhances the understanding of HIV VR prevalence and its contributing factors, while also providing recommendations to mitigate these factors.

Keywords: factors; prevalence; antiretroviral therapy; human immune deficiency virus; viral rebound.

Introduction

South Africa (SA) stands as the nation with the highest number of people living with human immune deficiency virus (HIV) globally.1 About 8 million people in the country are HIV-positive, and of all HIV-positive individuals, 62.3% are on antiretroviral therapy (ART).2 These numbers of people living with HIV made the country respond by implementing the most extensive ART campaign known as universal test and treat (UTT), which stipulates that regardless of cluster of differentiation 4 (CD4) cell count, all known HIV-positive patients begin first-line ART.3

The primary goals of ART are to reduce opportunistic infections and other HIV-associated diseases by maintaining viral suppression.4 Moreover, it reduces the chance of treatment resistance, improves the quality of life and is also used as a prophylactic precaution to reduce new infections.5 Antiretroviral therapy also reduces the mortality and morbidity caused by acquired immunodeficiency syndrome (AIDS) and HIV and improves people’s quality of life.5 Antiretroviral therapy helps to achieve and maintain viral suppression.5

Nonetheless, some individuals may experience severe viral rebound (VR) after achieving viral suppression.4 Even though ART services are rendered free of charge by the Department of Health (DoH) in SA to the population1,2 and despite the implementation of UTT, several factors continue to contribute to the ongoing global issue of HIV VR.1 Viral rebound is when two successive viral load measurements within a year show HIV-1 ribonucleic acid (RNA) of 50 copies/mL or > 50 copies/mL, respectively.6 There are several factors linked to VR, such as poor adherence,7 lower education level,8 lower health literacy9 and poorer quality of health care, including mistrust of medical providers.10 Other factors include substance use and HIV-related stigma,11 tuberculosis (TB)12 and the type of ART regimen.13 Kahabuka et al.14 found that participants with advanced HIV illness and shorter clinic visit intervals were more likely to experience VR within the first 2 years of ART.

Several studies have been conducted on HIV VR, and it is evident that VR is still prevalent. Liu et al.15 found that out of 3500 patients in the United States (US), 90% of patients had viral suppression, while 10% of patients had VR. Moreover, in Northern Tanzania, Kahabuka et al.14 revealed that among the recruited 416 people living with HIV on ART, 40% experienced VR. Maina et al.7 conducted a study that showed a high HIV VR rate in Kenya, with Meru having the highest rate (82%), followed by Malindi (81%) and Nakuru (12%). People living with HIV who achieve viral suppression are unable to sustain an undetectable viral load and experience VR, increasing the risk of HIV transmission.16 Liu et al.15 found that of patients in the US who had 2 years of sustained viral suppression, 10% suffered VR, and 4% experienced prolonged VR. The prevalence of HIV VR occurs in roughly 7.5% of people living with HIV who were able to achieve viral suppression.16

Several interventions ensure that people achieve and maintain viral suppression, such as a strategy to achieve sustained post-treatment control that involves eradicating the HIV reservoir or reducing its size so that effective viral reactivation from latency happens infrequently.17 Moreover, activating the latent virus and causing the immune system to eliminate infected cells on its own or through spontaneous means is one method of lowering the likelihood of HIV reactivation.18

The strategies used in SA to prevent HIV VR switching to second-line ART are defined as moving from non-nucleoside reverse transcriptase inhibitor (NNRTI)-containing ART to protease inhibitor (PI)-containing ART after viremia and intensifying health education,4 continuous monitoring of the viral load in people living with HIV is critical for treatment success and preventing transmission5,19,20,21 and minimising barriers to access ART.22

Even though many studies have been conducted on HIV VR and suppression, little focus has been put on systematic reviews examining the prevalence of VR and the contributing factors among individuals on ART. Hence, this study sought to conduct a systematic review to determine the prevalence of VR and the contributing factors among individuals on ART. Furthermore, the study aimed to identify and address gaps in the field and provide policymakers and stakeholders with new guidelines to support the maintenance of viral suppression once achieved and assist in the implementation of educational programmes that focus and raise awareness on preventing the occurrence of HIV VR among people living with HIV and their caregivers.

Methods

This review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines23 and the Cochrane Handbook for Systematic Reviews.24 The study was then registered with the International Prospective Register of Systematic Reviews (PROSPERO) on 07 May 2024, under the registration ID CRD42024524121.

Eligibility criteria
Inclusion criteria
  • This study included all peer-reviewed published articles that discuss HIV VR globally.
  • All English-written articles were included.
  • This review included articles published from 2012 onwards that addressed the HIV VR phenomenon.
Exclusion criteria
  • All non-peer-reviewed, published and non-scholar articles were excluded from the study.
  • All articles written in any other language except English were excluded.
  • The articles not related to the phenomenon of VR were excluded and articles published in 2011 or earlier were excluded.
Participants

The researcher used only English-written, peer-reviewed and globally published articles on HIV VR.

Information sources

The data were sourced from PubMed, EBSCOhost and Scopus. The data search started in March 2024 and ended in May 2024, and to ensure recent data were sourced, the review included studies published from 2012 to 2024.

Search strategy

This study mainly focused on secondary data collection, which was retrieved from PubMed, EBSCOhost and Scopus. The data search started in March 2024 and ended in May 2024; the researcher initially collected data on a total of 89 684 articles, of which 33 585 were from PubMed, 5167 were from EBSCOhost and 50 932 were from Scopus (see Figure 1).25

FIGURE 1: Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) diagram illustrating the screening process.

The data were searched using the keywords ‘factors’; ‘prevalence’; ‘antiretroviral therapy; antiretroviral’; ‘human immune deficiency virus; ‘highly active antiretroviral therapy’; and ‘viral rebound’. Only English-written, peer-reviewed, globally, sub-Saharan African (SSA) and South African published articles were used; only studies from the year 2012 and above were included; articles were scanned and skimmed; all searched articles were saved in a folder; and any duplicated information was deleted. The main researcher used Rayyan software to include and exclude studies.

Data collection, selection and extraction process

A total of 89 684 articles were imported into Rayyan for screening, sourced from PubMed (33 585 articles), EBSCOhost (5167 articles) and Scopus (50 932 articles), and the Rayyan software identified 60 201 duplicates, of which 40 297 were deleted and 60 201 were resolved, leading to the exclusion of 47 655 articles. Additionally, 1509 articles remained undecided, while 223 articles were included in the first screening cycle based on their topic relevance. In the second round of exclusions, the main researcher applied the study’s predefined inclusion and exclusion criteria, mainly focusing on the publication year; as a result, all studies published prior to 2012 were excluded from the pool of 1509 undecided articles, reducing the number by 586 and leaving 923 articles for further consideration. Among the 223 articles initially included based on topic relevance, 42 studies were subsequently excluded, so 181 articles remained for further evaluation.

The third round of exclusions focused on assessing the relevance of the articles to the study, which led to the exclusion of 855 articles from the 923 undecided studies, and as a result, 68 articles were retained for inclusion, bringing the total number of included articles to 249 when combined with the 181 articles included in the previous round. In the fourth round, the remaining 249 articles were further analysed, and during this process, 214 articles were excluded, narrowing the selection to 35 articles for eligibility reassessment; after reassessing eligibility, 12 additional articles were excluded because of irrelevance, leaving a final selection of 23 eligible articles (see Figure 1). The selected studies were assessed for eligibility and reviewed with the three supervisors and a conclusion was drawn.

Quality assessment

All included articles were assessed using Joanna Briggs Institute’s (JBI’s) quality appraisal framework7 (see Table 1). All articles included in this systematic review clearly outlined their aims and objectives, methodology, and research design.

TABLE 1: Summary table of selected studies.
TABLE 1 (Continues…): Summary table of selected studies.
TABLE 1 (Continues…): Summary table of selected studies.
TABLE 1 (Continues…): Summary table of selected studies.
TABLE 1 (Continues…): Summary table of selected studies.
TABLE 1 (Continues…): Summary table of selected studies.
TABLE 1 (Continues…): Summary table of selected studies.
TABLE 1 (Continues…): Summary table of selected studies.
TABLE 1 (Continues…): Summary table of selected studies.
TABLE 1 (Continues…): Summary table of selected studies.
Ethical considerations

This study used secondary data; however, Sefako Makgatho Health Sciences Ethics Committee (SMUREC) (Reference Number: SMUREC/H/464/2023: PG) provided ethical clearance and permission for the project. The systematic review was registered on PROSPERO (International Register of Systematic Reviews; CRD42024524121).

Results

Among the 23 studies included in this review, 13 studies discuss the prevalence of HIV VR. The findings across these studies indicate considerable variability in VR prevalence, influenced by factors such as population characteristics, geographic region and ART regimens.

From the analysis of the table presented in the studies, it is evident that genetics and biological factors emerge as the most significant drivers of HIV VR. Genetic predispositions, along with factors such as drug–drug interactions (DDIs), co-infections and medication interactions, contribute substantially to the persistence of the virus and its ability to rebound after treatment interruption. These biological factors remain central to understanding the dynamics of HIV VR, as they directly influence the virus’s ability to persist in the body, even under ART.

In addition, socio-economic and structural barriers are identified as the second-largest contributors to HIV VR. Factors such as low socio-economic status, unstable housing, lack of access to health care and incarceration significantly impact an individual’s ability to adhere to treatment regimens and attend necessary follow-up appointments. These structural challenges create an environment that makes effective HIV management more difficult, thereby increasing the risk of VR.

Demographic factors, particularly age, also play a critical role in determining the likelihood of HIV VR. Research consistently shows that younger age is associated with a higher risk of VR, potentially because of lower adherence rates, less consistent engagement in care and possibly immune system dynamics that differ from older populations. This underscores the need for targeted interventions for younger individuals, as they may face unique challenges in managing HIV effectively.

Additionally, behavioural and lifestyle factors are found to contribute to the risk of HIV VR significantly. Increased likelihood of VR has been associated with substance use, including alcohol and drug abuse, as well as high-risk behaviours such as having multiple sexual partners or engaging in travel during ART treatment, have all been linked to. These factors disrupt the consistency of ART adherence and can impair immune system function, further complicating the management of HIV.

Finally, treatment and clinical management factors, particularly poor adherence to ART, are significant drivers of HIV VR. Non-adherence, whether because of forgetfulness, dissatisfaction with treatment regimens, or other personal and logistical barriers, remains among the most substantial contributors to VR. The ability to effectively manage ART, including ensuring proper drug regimen adherence and timely follow-up appointments, is crucial in preventing the occurrence of VR.

Therefore, the drivers of HIV VR are multifaceted, involving a complex interplay of genetic, socio-economic, demographic, behavioural and clinical management factors. Understanding these diverse influences is essential for developing comprehensive strategies aimed at reducing the risk of HIV VR and improving long-term treatment outcomes.

Characteristics of selected studies

Table 1 provides a summary of selected studies in this review. This review included 23 studies based on predefined selection criteria. The studies were sourced from three academic data sources: 15 from PubMed, 8 from Scopus and 1 from EBSCOhost. Most studies are non-African published, representing 83% of the sample. Thirteen per cent of studies are from SSA and 4% of studies originate from SA. The 4% of studies on HIV VR in SA indicate a notable gap in research on this topic over the past decade.

The studies included in this review were published between 2016 and 2024. The distribution of publications across years is as follows: 30.43% of studies were published in 2020, 21.74% of studies were published in 2019 and 17.39% of studies were published in 2016. Among the remaining publications, 13.04% were published in 2022, with an additional 4.35% published in each of the years 2017, 2018, 2023, and 2024.

The studies in this review employed a range of methodological approaches. The majority were retrospective cohort studies, with six studies using this design. Three prospective cohort studies followed this, and two cross-sectional studies and two case reports. Other study designs included one each of the following: clinical trial, clinical trial and observational study, cross-sectional and longitudinal study, longitudinal study, laboratory-based study, longitudinal cohort study, longitudinal observational study, mixed-methods, randomised controlled trial and theoretical model study.

The PRISMA diagram (Figure 1) illustrates the screening process followed in this study for HIV VR research, thus ensuring transparency.

Discussion

Research consistently demonstrates that the prevalence of HIV VR remains a significant public health concern, with notable variability in prevalence across different populations. These findings align with those of previous studies, such as the research by Rosen et al.46 which reported that only 2.5% of people living with HIV experienced VR. In a study by Bansi et al.47 higher rates of VR were observed in individuals who had previously discontinued treatment, with a rate ratio of 1.64 (1.43–1.88), and the total VR rate for every 100 person-years was calculated at 8.07 (7.78–8.36).

Similarly, research by Bridges et al.48 found that the cumulative incidence of VR 1 year after achieving viral suppression varied across different ethnic groups, with 13% of Indigenous Caucasian individuals; 7% of African, Caribbean and black (ACB) individuals; and 5% of both other ethnic groups and individuals of unknown ethnicity experiencing rebound. However, a study by Grabowski et al.49 showed a significant reduction in VR and chronic viremia with the implementation of UTT strategies. In their research, Grabowski et al.49 discovered that the prevalence of VR decreased from 4.4% to 2.7%, while chronic viremia dropped from 20.8% to 13.3%. These studies highlight the ongoing challenge of managing VR and underscore the need for tailored approaches to HIV treatment that account for demographic, treatment and health care-related factors.

Research has revealed that HIV VR is genetically linked, which is consistent with findings from Cole et al.29 that show that latently infected cells can become activated and produce the virus once ART is discontinued. Vallejo et al.50 demonstrated that the TLR9-1635AA genotype is independently associated with an increased risk of HIV VR following the cessation of ART.

However, not all studies support the view that genetic factors are pivotal in HIV VR. Mpolya1 highlighted that patient-specific variables and treatment adherence may significantly influence VR. Similarly, Thorball et al.51 found no meaningful correlation between human genetic variation and the size of the HIV reservoir or its rate of decay after suppressive ART, which raises questions about the role of genetics in the dynamics of HIV VR. These mixed findings highlight the complexity of the relationship between host genetics and HIV VR, suggesting that further investigation is needed to understand better the extent to which genetic factors contribute to VR.

The findings demonstrate a strong association between the type of ART regimen and HIV VR. Childs et al.52 suggest that the choice of first-line ART influences the outcomes following VR. Furthermore, Liu et al.15 found that individuals on integrase strand transfer inhibitors (INSTIs) exhibited a higher likelihood of VR. In contrast, Boucoiran et al.53 found no discernible correlation between the type of ART regimen and HIV VR, implying that ART regimen choice may not significantly affect the incidence of VR.

The study finds that HIV VR is associated with DDIs and drug resistance. This finding is consistent with previous research by Rock et al.54 Patients taking INSTIs such as bictegravir may experience VR because of DDIs with divalent cations like calcium and zinc. Furthermore, Kumar et al.55 stated that DDIs, particularly those affecting the induction or inhibition of the cytochromes P450 (CYP) enzyme, can reduce the bioavailability of ART, thereby increasing viral load and diminishing the efficacy of ART, and this can result in HIV VR in affected individuals.

However, Iniesta-Navalón et al.56 reported that DDIs did not significantly impact viral load outcomes in their observed patient population. These findings underscore the complexity of HIV VR, highlighting the interplay between drug resistance, DDIs and immune response in determining viral outcomes. While DDIs and drug resistance may contribute to VR, immune factors also play a pivotal role in viral dynamics.

The study found that co-infections, particularly TB and syphilis, are significant contributors to VR in people living with HIV, which is consistent with findings from another research. For instance, co-infections such as acute malaria and active TB also contribute to VR, with acute malaria associated with a 0.67 log10 increase and active TB linked to a 0.40 log10 rise in HIV viral load.57 Additionally, the presence of multiple viral infections may create complex interactions at the cellular level, which can enhance HIV replication and contribute to VR.58 These dynamics highlight the need for effective management of co-infections to prevent VR and slow HIV progression.

The study finds that HIV VR is associated with low socioeconomical status (SES), which is consistent with the findings from previous research. Abgrall et al.59 linked a higher risk of VR to low educational attainment, poor financial conditions and non-disclosure of HIV status. Liu et al.15 stated that SES, employment and food security are risk factors for VR. However, López et al.60 found that SES was insignificant in HIV VR. This divergence highlights the complexity of the relationship between socio-economic factors and HIV VR, suggesting that further research is needed to clarify their precise role and impact.

The study identifies a history of incarceration as a significant factor contributing to VR, a finding that aligns with prior research. Periods of incarceration often disrupt individuals’ ART regimens, leading to breaks in therapy that are correlated with a heightened risk of VR.61 Similarly, Westergaard et al.62 emphasised that incarceration is linked to poorer treatment outcomes, further highlighting the detrimental effects of incarceration on HIV care and viral suppression. These disruptions underscore the challenges faced by individuals transitioning in and out of incarceration, which can undermine the effectiveness of ART and contribute to VR.

The study finds that VR is strongly associated with patient loss to follow-up, which aligns with several prior studies. Hao63 reported higher rates of VR among youth with HIV who missed appointments compared to those who remained engaged in regular care. Additionally, a study by Sethi et al.64 showed that the risk of VR, often coupled with clinically significant resistance, was independently associated with missed clinic visits.

The research indicates that alcohol and substance use are significant factors contributing to the development of HIV VR. These findings are consistent with those of Tanner et al.65 who found an association between VR and injectable drug use. At the same time, Liu et al.15 found that smoking is associated with VR. However, Wynn et al.66 observed a negative correlation between alcohol use and adherence to ART, although this association was not statistically significant in terms of viral load suppression.

The study highlights a significant association between HIV VR and travel, aligning with other researchers’ findings. Travel can impede adherence to ART in people living with HIV, leading to ART interruptions and an increased risk of VR.67 However, Joos et al.68 suggested that travel itself may not be the primary cause of VR, as it is typically because of the reactivation of latent HIV reservoirs rather than sustained low-level replication. This discourse reflects the complexity of the relationship between travel and HIV VR, suggesting that while travel may be a contributing factor, other underlying biological mechanisms must also be considered.

The study finds that having multiple sexual partners and engaging in risky sexual behaviour contribute to HIV VR, which aligns with the findings of other researchers. Risk compensation behaviours where individuals engage in riskier sexual practices because they believe ART will protect them have been reported to increase the risk of sexually transmitted infections (STIs) and VR.69

Therefore, while multiple and concurrent sexual partnerships are a key factor in the spread of HIV, more research is needed to fully understand the interplay between sexual behaviour, ART adherence and VR. These findings highlight the multifaceted nature of HIV transmission, emphasising the need for targeted prevention strategies that address both behavioural risks and the challenges of maintaining viral suppression.

The study identifies poor adherence or non-compliance as a key factor contributing to HIV VR, a finding consistent with previous research. Achappa et al.70 reported that VR, continued immunosuppression and viral resistance can result from non-adherence to ART. However, Maggiolo et al.71 suggested that while mild non-adherence to ART may not necessarily result in virologic failure or VR, it is often associated with low-level residual viremia. These findings underscore the critical role of consistent adherence in preventing virologic failure and ensuring long-term viral suppression.

The study finds that HIV VR is associated with pre-ART conditions and HIV staging, which aligns with findings from previous research. For instance, Castagna et al.72 observed a significant correlation between pre-ART factors and the magnitude of VR. According to Robertson et al.73 VR is more likely in individuals who had an initial CD4 count ≥ 350 at diagnosis or those diagnosed with AIDS. Similarly, Ceccherini-Silberstein et al.74 reported that a higher level of pre-ART HIV deoxyribonucleic acid (DNA) was associated with an increased likelihood of VR.

This study identifies gender as a contributing factor to HIV VR, which aligns with several other research findings. In particular, several studies have suggested that women are less likely than men to experience HIV VR.75 However, Adams et al.76 found no significant correlation between female sex and the occurrence of HIV VR. Furthermore, men who have sex with men (MSM) born in France did not confer a higher risk of HIV VR compared to heterosexual individuals born in France.59 Suggesting that gender alone is not a determining factor in VR risk. Thus, these studies collectively highlight the complexity of gender as a variable in HIV VR, with conflicting results that warrant further investigation.

The study finds that black individuals are disproportionately affected by VR, a finding that aligns with several previous studies. For instance, Dhairyawan et al.77 reported that Asian and black populations were more likely to experience VR compared to white individuals, further underscoring racial disparities in HIV outcomes. Similarly, Liu et al.15 identified race as a significant factor associated with HIV-related VR. Notably, Liu et al.15 also observed that among people living with HIV who had previously achieved sustained viral suppression, race remained correlated with the likelihood of experiencing VR. Collectively, these findings suggest that black individuals may be particularly vulnerable to VR. However, while race appears to be an important factor, it is essential to acknowledge that broader social, behavioural and medical determinants also contribute to these disparities.

Studies have shown that HIV VR is associated with younger age, a finding consistent with11,13,14,15,16,17 all of who identified a higher likelihood of HIV VR in younger individuals compared to older populations. The independent correlates of viral suppression and VR for younger adults are similar to those affecting older individuals, suggesting that age alone may not fully account for variations in VR outcomes.

Strength and limitations

One of the primary strengths of this systematic review was its rigorous methodology, following a structured and transparent process for identifying, selecting and synthesising studies. Using multiple data sources like PubMed, Scopus and EBSCOhost ensured a broad scope and minimised bias. The systematic approach to study selection and data extraction increased the reliability of findings, while including diverse studies provided a general understanding of HIV VR. Narrative synthesis and the PRISMA flow diagram enhanced clarity and assessing study quality and risk of bias ensured conclusions were based on strong evidence, offering insights into HIV VR prevalence and contributing factors.

However, several limitations should be noted. The review was restricted to studies in English, potentially introducing language bias. Some studies lacked detailed reporting on key variables, limiting full validity evaluation. Only Department of Higher Education and Training (DHET) accredited journals were included, excluding grey literature and unpublished studies, and strict inclusion criteria limited studies to those published from 2012 onwards. These factors may have caused publication bias and incomplete findings on HIV VR.

Recommendations

Health care providers should be trained to recognise and address HIV VR factors, including ART non-adherence, interruptions and suboptimal regimens, using evidence-based information to enhance personalised care and timely interventions. Targeted interventions for high-risk groups like youth, substance users and those with socio-economic challenges are necessary, alongside integrating mental health care and harm reduction into ART programmes. Addressing socio-economic barriers with financial, educational and social support improves access to care for marginalised populations. High-risk groups, including black individuals, MSM and youth, should receive community-based programmes and culturally competent care to improve HIV care engagement. Personalising ART regimens based on patient history and resistance testing optimises treatment outcomes, while regular screening for co-infections like TB and STIs helps maintain viral suppression and prevent VR.

Uninterrupted HIV care during and after incarceration is crucial for reducing treatment interruptions. Pre-travel counselling and support are important for maintaining adherence during travel. Ongoing research into the biological, behavioural and social factors of HIV VR is necessary to develop effective prevention strategies. Public health campaigns should raise awareness about ART adherence, regular healthcare visits and care engagement, focusing on at-risk populations and reducing stigma to improve HIV management and reduce VR.

Conclusion

The study finds that the prevalence of HIV VR varies across different populations. Moreover, HIV VR is influenced by a complex interplay of behavioural, socio-economic, demographic, medical and environmental factors. While certain factors, such as ART regimen choices, alcohol use, treatment adherence, age, co-infections and DDIs, show consistent associations with VR, there is still much to learn about the relative importance of these variables and their interactions. Further research is necessary to disentangle these factors and to develop targeted interventions that address the diverse challenges faced by individuals living with HIV to reduce the risk of VR and improve long-term health outcomes.

Acknowledgements

The authors would like to thank the first author (L.N.) for the design of Table 1.

Competing interests

The authors declare that they have no financial or personal relationships that may have inappropriately influenced them in writing this article.

Authors’ contributions

L.N. contributed to developing the structure and approach of the study, as well as collecting secondary data from EBSCOhost, Scopus and PubMed; conducted the analysis; and wrote the original article. R.J.S. reviewed and edited the first draft of the article. M.M.M., L.P.C. and R.J.S. supervised the study, reviewed and proofread the second draft of the article and provided final approval. All authors have read and approved the final article.

Funding information

This research did not receive funding from any public, commercial or not-for-profit organisations.

Data availability

This review was carried out using secondary data, that is, data from published articles. The data sources PubMed, Scopus and EBSCOhost were utilised. Data sharing is not applicable to this article, as no new data were created or analysed in this study.

Disclaimer

The views and opinions expressed in this study are those of the authors and are the product of professional research. They do not necessarily reflect the official policy or position of any affiliated institution, funder, agency or that of the publisher. The authors are responsible for this study’s results, findings and content.

References

  1. Mpolya E. A prospective study of predictors of HIV viral load rebound in an HIV hyperendemic rural population of KwaZulu-Natal, South Africa. PAMJ-One Health. 2023;11:13. https://doi.org/10.11604/pamj-oh.2023.11.13.40381
  2. Simbayi L, Zuma K, Zungu N, et al. South African National HIV prevalence, incidence, behaviour and communication survey, 2017: Towards achieving the UNAIDS 90-90-90 targets. Cape Town: HSRC Press; 2019 [cited 2025 Jul 04]. Available from: https://repository.hsrc.ac.za/handle/20.500.11910/15052
  3. Hirasen K, Fox MP, Hendrickson CJ, et al. HIV treatment outcomes among patients initiated on antiretroviral therapy pre and post-universal test and treat guidelines in South Africa. Ther Clincal Risk Manag. 2020;16:169–180. https://doi.org/10.2147/TCRM.S227290
  4. Günthard HF, Saag MS, Benson CA, et al. Antiretroviral drugs for treatment and prevention of HIV infection in adults: 2016 recommendations of the International Antiviral Society–USA panel. JAMA. 2016;316:191–210. https://doi.org/10.1001/jama.2016.8900
  5. Eggleton JS, Nagalli S. Highly Active Antiretroviral Therapy (HAART). Treasure Island, FL: StatPearls Publishing; 2023.
  6. Geretti AM, Smith C, Haberl A, et al. Determinants of virological failure after successful viral load suppression in first-line highly active antiretroviral therapy. Antivir Ther. 2008;13:927–936. https://doi.org/10.1177/135965350801300707
  7. Maina E, Mureithi H, Adan A, et al. Incidences and factors associated with viral suppression or rebound among HIV patients on combination antiretroviral therapy from three counties in Kenya. Int J Infect Dis. 2020;97:151–158. https://doi.org/10.1016/j.ijid.2020.05.097
  8. Min S, Gillani FS, Aung S, et al. Evaluating HIV viral rebound among persons on suppressive antiretroviral treatment in the era of ‘undetectable equals untransmittable (U= U)’. Open Forum Infect Dis. 2020;7(12):ofaa529.
  9. Baumann KE, Phillips AL, Arya M. Overlap of HIV and low health literacy in the southern USA. Lancet HIV. 2015;2:e269. https://doi.org/10.1016/S2352-3018(15)00121-6
  10. Gaston GB, Alleyne-Green B. The impact of African Americans’ beliefs about HIV medical care on treatment adherence: A systematic review and recommendations for interventions. AIDS Behav. 2013;17:31–40. https://doi.org/10.1007/s10461-012-0323-x
  11. Geter A, Herron AR, Sutton MY. HIV-related stigma by healthcare providers in the United States: A systematic review. AIDS Patient Care STDs. 2018;32:418–424. https://doi.org/10.1089/apc.2018.0114
  12. Kassa D, Gebremichael G, Alemayehu Y, et al. Virologic and immunologic outcome of HAART in Human Immunodeficiency Virus (HIV)-1 infected patients with and without tuberculosis (TB) and latent TB infection (LTBI) in Addis Ababa, Ethiopia. AIDS Res Ther. 2013;10:1–12. https://doi.org/10.1186/1742-6405-10-18
  13. Horter S, Thabede Z, Dlamini V, et al. ‘Life is so easy on ART, once you accept it’: Acceptance, denial and linkage to HIV care in Shiselweni, Swaziland. Soc Sci Med. 2017;176:52–59. https://doi.org/10.1016/j.socscimed.2017.01.006
  14. Kahabuka MS, Woldeamanuel Y, Mbelele PM, et al. HIV viral suppression and risk of viral rebound in patients on antiretroviral therapy: A two-year retrospective cohort study in Northern Tanzania. BMC Infect Dis. 2024;24:390. https://doi.org/10.1186/s12879-024-09161-y
  15. Liu T, Chambers LC, Hansen B, et al. Risk of HIV viral rebound in the era of universal treatment in a multicenter sample of persons with HIV in primary care. Open Forum Infect Dis. 2023;10(6):ofad257.
  16. Craw JA, Beer L, Tie Y, et al. Viral rebound among persons with diagnosed HIV who achieved viral suppression, United States. J Acquir Immune Defic Syndr. 2020;84:133–140. https://doi.org/10.1097/QAI.0000000000002321
  17. Cromer D, Pinkevych M, Rasmussen TA, et al. Modeling of antilatency treatment in HIV: What is the optimal duration of antiretroviral therapy-free HIV remission? J Virol. 2017;91(24):e01395-17. https://doi.org/10.1128/JVI.01395-17
  18. Deeks SG, Archin N, Cannon P, et al. Research priorities for an HIV cure: International AIDS society global scientific strategy 2021. Nat Med. 2021;27:2085–2098. https://doi.org/10.1038/s41591-021-01590-5
  19. Chinuoya M, Rikhotso R, Ngunyulu RN, et al. Some mix it with other things to smoke’: Perceived use and misuse of ARV by street thugs in Tshwane District, South Africa. Afr J Phys Health Edu Recreat Dance. 2014;1(1):113–126.
  20. Hermans LE, Carmona S, Nijhuis M, et al. Virological suppression and clinical management in response to viremia in South African HIV treatment program: A multicenter cohort study. PLoS Med. 2020;17:e1003037. https://doi.org/10.1371/journal.pmed.1003037
  21. Hans L, Cassim N, Sarang S, et al. HIV viral load testing in the South African public health setting in the context of evolving ART guidelines and advances in technology, 2013–2022.c Diagnostics. 2023;13:2731. https://doi.org/10.3390/diagnostics13172731
  22. Zhou S, Cluver L, Shenderovich Y, et al. Uncovering ART adherence inconsistencies: An assessment of sustained adherence among adolescents in South Africa. J Int AIDS Soc. 2021;24(10):e25832. https://doi.org/10.1002/jia2.25832
  23. Moher D, Liberati A, Tetzlaff J, et al. Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. Int J Surg. 2010;8:336–341. https://doi.org/10.1016/j.ijsu.2010.02.007
  24. Chandler J, Cumpston M, Li T, et al. Cochrane handbook for systematic reviews of interventions. Hoboken, NJ: Wiley; 2019.
  25. Page MJ, McKenzie JE, Bossuyt PM, et al. The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ. 2021;372:n71. https://doi.org/10.1136/bmj.n71
  26. Aamer HA, McClure J, Ko D, et al. Cells producing residual viremia during antiretroviral treatment appear to contribute to rebound viremia following interruption of treatment. PLoS Pathog. 2020;16(8):e1008791. https://doi.org/10.1371/journal.ppat.1008791
  27. Armenia D, Di Carlo D, Cozzi-Lepri A, et al. Very high pre-therapy viral load is a predictor of virological rebound in HIV-1-infected patients starting a modern first-line regimen. Antivir Ther. 2019;24(5):321–331. https://doi.org/10.3851/IMP3309
  28. Burch LS, Smith CJ, Anderson J, et al. Socioeconomic status and treatment outcomes for individuals with HIV on antiretroviral treatment in the UK: Cross-sectional and longitudinal analyses. Lancet Public Health. 2016;1(1):e26–e36. https://doi.org/10.1016/S2468-2667(16)30002-0
  29. Cole B, Lambrechts L, Boyer Z, et al. Extensive characterization of HIV-1 reservoirs reveals links to plasma viremia before and during analytical treatment interruption. Cell Rep. 2022;39(4):110739. https://doi.org/10.1016/j.celrep.2022.110739
  30. De Scheerder MA, Vrancken B, Dellicour S, et al. HIV rebound is predominantly fueled by genetically identical viral expansions from diverse reservoirs. Cell Host Microbe. 2019;26(3):347–358. https://doi.org/10.1016/j.chom.2019.08.003
  31. Dessie ZG, Zewotir T, Mwambi H, North D. Modeling viral suppression, viral rebound and state-specific duration of HIV patients with CD4 count adjustment: Parametric multistate frailty model approach. Infect Dis Ther. 2020;9:367–388. https://doi.org/10.1007/s40121-020-00296-4
  32. Gebreselassie HM, Kraus D, Fux CA, et al. Ethnicity predicts viral rebound after travel to the tropics in HIV-infected travelers to the tropics in the Swiss HIV cohort study. HIV Med. 2017;18(8):564–572. https://doi.org/10.1111/hiv.12491
  33. Giacomelli A, Micheli V, Cattaneo D, Mancon A, Gervasoni C. Multidrug-resistant HIV viral rebound during early syphilis: A case report. BMC Infect Dis. 2020;20:1–5. https://doi.org/10.1186/s12879-020-04999-4
  34. Hayashi R, Hara A, Iwasa Y. Viral rebound occurrence immediately after drug discontinuation involving neither drug resistance nor latent reservoir. J Theor Biol. 2024;582:111767. https://doi.org/10.1016/j.jtbi.2024.111767
  35. Jones TP, Lampe FC, Arenas-Pinto A, et al. Alcohol, smoking, recreational drug use and association with virological outcomes among people living with HIV: Cross-sectional and longitudinal analyses. HIV Med. 2022;23(3):209–26. https://doi.org/10.1111/hiv.13156
  36. Kang-Birken SL, El-Sayed D, Prichard J. HIV viral rebound due to a possible drug–drug interaction between elvitegravir/cobicistat/emtricitabine/tenofovir alafenamide and calcium-containing products: Report of 2 cases. J Int Assoc Provid AIDS Care. 2019;18:2325958218821653. https://doi.org/10.1177/2325958218821653
  37. Kankou JM, Bouchaud O, Lele N, et al. Factors associated with virological rebound in HIV-positive Sub-Saharan Migrants living in France after traveling back to their native country: ANRS-VIHVO 2006–2009 study. J Immigr Minor Health. 2019;21:1342–1348. https://doi.org/10.1007/s10903-019-00864-y
  38. Ladak F, Socias E, Nolan S, et al. Substance use patterns and HIV-1 RNA viral load rebound among HIV-positive illicit drug users in a Canadian setting. Antivir Ther. 2019;24(1):19–25. https://doi.org/10.3851/IMP3265
  39. Megasari NL, Wijaksana IK. Factors affecting HIV viral load of antiretroviral therapy experienced and naïve individuals residing in Bali, Indonesia. Mal J Med Health Sci. 2023;19:111–115.
  40. Mujugira A, Celum C, Tappero JW, Ronald A, Mugo N, Baeten JM. Younger age predicts failure to achieve viral suppression and virologic rebound among HIV-1-infected persons in serodiscordant partnerships. AIDS Res Hum Retroviruses. 2016;32(2):148–154. https://doi.org/10.1089/aid.2015.0296
  41. Offersen R, Yu WH, Scully EP, et al. HIV antibody Fc N-linked glycosylation is associated with viral rebound. Cell Rep. 2020;33(11):108502. https://doi.org/10.1016/j.celrep.2020.108502
  42. Opoku S, Sakyi SA, Ayisi-Boateng NK, et al. Factors associated with viral suppression and rebound among adult HIV patients on treatment: A retrospective study in Ghana. AIDS Res Ther. 2022;19(1):21. https://doi.org/10.1186/s12981-022-00447-2
  43. Palmer A, Gabler K, Rachlis B, et al. Viral suppression and viral rebound among young adults living with HIV in Canada. Medicine. 2018;97(22):e10562. https://doi.org/10.1097/MD.0000000000010562
  44. Small W, Milloy MJ, McNeil R, Maher L, Kerr T. Plasma HIV-1 RNA viral load rebound among people who inject drugs receiving antiretroviral therapy (ART) in a Canadian setting: An ethno-epidemiological study. AIDS Res Ther. 2016;13:1–2. https://doi.org/10.1186/s12981-016-0108-9
  45. Stöhr W, Dunn DT, Arenas-Pinto A, et al. Factors associated with virological rebound in HIV-infected patients receiving protease inhibitor monotherapy. AIDS. 2016;30(17):2617–2624. https://doi.org/10.1097/QAD.0000000000001206
  46. Rosen JG, Ssekubugu R, Chang LW, et al. Temporal dynamics and drivers of durable HIV viral load suppression and persistent high-and low-level viraemia during Universal Test and Treat scale-up in Uganda: A population-based study. J Int AIDS Soc. 2024;27:e26200. https://doi.org/10.1002/jia2.26200
  47. Bansi LK, Benzie AA, Phillips AN, et al. Are previous treatment interruptions associated with higher viral rebound rates in patients with viral suppression? AIDS (London, England). 2008;22:349–356. https://doi.org/10.1097/QAD.0b013e3282f4709a
  48. Bridges B, Collaboration COC, Benoit AC, et al. A comparison of virological suppression and rebound between Indigenous and non-Indigenous persons initiating combination antiretroviral therapy in a multisite cohort of individuals living with HIV in Canada. Antivir Ther. 2017;22:325–335. https://doi.org/10.3851/IMP3114
  49. Grabowski MK, Patel EU, Nakigozi G, et al. Prevalence and predictors of persistent human immunodeficiency virus viremia and viral rebound after universal test and treat: A population-based study. J Infect Dis. 2021;223:1150–1160. https://doi.org/10.1093/infdis/jiab021
  50. Vallejo A, Molina-Pinelo S, De Felipe B, et al. Brief report: Toll-like receptor 9-1635A/G polymorphism is associated with HIV-1 rebound after four weeks of interruption of antiretroviral therapy. J Acquir Immune Defic Syndr. 2020;85:252–256. https://doi.org/10.1097/QAI.0000000000002437
  51. Thorball CW, Borghesi A, Bachmann N, et al. Host genomics of the HIV-1 reservoir size and its decay rate during suppressive antiretroviral treatment. J Acquir Immune Defic Syndr. 2020;85:517–524. https://doi.org/10.1097/QAI.0000000000002473
  52. Childs T, Shingadia D, Goodall R, et al. Outcomes after viral load rebound on first-line antiretroviral treatment in children with HIV in the UK and Ireland: An observational cohort study. Lancet HIV. 2015;2:e151–e158. https://doi.org/10.1016/S2352-3018(15)00021-1
  53. Boucoiran I, Albert AY, Tulloch K, et al. Human immunodeficiency virus viral load rebound near delivery in previously suppressed, combination antiretroviral therapy–treated pregnant women. Obstetr Gynecol. 2017;130:497–501. https://doi.org/10.1097/AOG.0000000000002133
  54. Rock AE, DeMarais PL, Vergara-Rodriguez PT, et al. HIV-1 virologic rebound due to coadministration of divalent cations and bictegravir. Infect Dis Ther. 2020;9:691–696. https://doi.org/10.1007/s40121-020-00307-4
  55. Kumar S, Rao P, Earla R, et al. Drug–drug interactions between anti-retroviral therapies and drugs of abuse in HIV systems. Expert Opin Drug Metab Toxicol. 2015;11:343–355. https://doi.org/10.1517/17425255.2015.996546
  56. Iniesta-Navalón C, Franco-Miguel JJ, Gascón-Cánovas JJ, et al. Effect of drug interactions involving antiretroviral drugs on viral load in HIV population. Eur J Hosp Pharm. 2016;23:241–243. https://doi.org/10.1136/ejhpharm-2015-000670
  57. Barnabas RV, Webb EL, Weiss HA, et al. The role of coinfections in HIV epidemic trajectory and positive prevention: A systematic review and meta-analysis. AIDS. 2011;25:1559–1573.
  58. Acchioni C, Sandini S, Acchioni M, et al. Co-Infections and superinfections between HIV-1 and other human viruses at the cellular level. Pathogens. 2024;13:349. https://doi.org/10.3390/pathogens13050349
  59. Study AC-C. Elevated risk of viral rebound on ART in migrants living in France: Role of socioeconomic factors. Antivir Ther. 2019;24:541–552. https://doi.org/10.3851/IMP3339
  60. López JD, Qiao Q, Presti RM, et al. The impact of neighborhood socioeconomic status on retention in care and viral suppression among people living with HIV. AIDS Care. 2022;34:1383–1389. https://doi.org/10.1080/09540121.2022.2040724
  61. Wohl DA, Rosen DL. Inadequate HIV care after incarceration: Case closed. Lancet HIV. 2018;5:e64–e65. https://doi.org/10.1016/S2352-3018(17)30210-2
  62. Westergaard RP, Kirk GD, Richesson DR, et al. Incarceration predicts virologic failure for HIV-infected injection drug users receiving antiretroviral therapy. Clin Infect Dis. 2011;53:725–731. https://doi.org/10.1093/cid/cir491
  63. Hao J. Navigating missed visits in HIV primary care: Exploring risk factors associated with missed visits. Birmingham: The University of Alabama at Birmingham; 2023.
  64. Sethi AK, Celentano DD, Gange SJ, et al. Association between adherence to antiretroviral therapy and human immunodeficiency virus drug resistance. Clin Infect Dis. 2003;37:1112–1118. https://doi.org/10.1086/378301
  65. Tanner Z, Lachowsky N, Ding E, et al. Predictors of viral suppression and rebound among HIV-positive men who have sex with men in a large multi-site Canadian cohort. BMC Infect Dis. 2016;16:1–11. https://doi.org/10.1186/s12879-016-1926-z
  66. Wynn A, Sileo KM, Schmarje Crockett K, et al. Associations between alcohol use, antiretroviral therapy use, and viral load suppression among people living with HIV in rural central Uganda. AIDS Behav. 2024;28:2205–2215. https://doi.org/10.1007/s10461-024-04299-x
  67. Apenteng OO, Ismail NA. Modelling the impact of international travellers on the trend of HIV epidemic. In: Proceedings of the world congress on engineering and computer science. 2014.
  68. Joos B, Fischer M, Kuster H, et al. HIV rebounds from latently infected cells, rather than from continuing low-level replication. Proc Natl Acad Sci USA. 2008;105:16725–16730. https://doi.org/10.1073/pnas.0804192105
  69. Bruce D, Harper GW, Suleta K, et al. Sexual risk behavior and risk reduction beliefs among HIV-positive young men who have sex with men. AIDS Behav. 2013;17:1515–1523. https://doi.org/10.1007/s10461-012-0155-8
  70. Achappa B, Madi D, Bhaskaran U, et al. Adherence to antiretroviral therapy among people living with HIV. N Am J Med Sci. 2013;5(3):220. https://doi.org/10.4103/1947-2714.109196
  71. Maggiolo F, Di Filippo E, Comi L, et al. Reduced adherence to antiretroviral therapy is associated with residual low-level viremia. Pragmat Obs Res. 2017;8:91–97. https://doi.org/10.2147/POR.S127974
  72. Castagna A, Muccini C, Galli L, et al. Analytical treatment interruption in chronic HIV-1 infection: Time and magnitude of viral rebound in adults with 10 years of undetectable viral load and low HIV-DNA (APACHE study). J Antimicrob Chemother. 2019;74:2039–2046. https://doi.org/10.1093/jac/dkz138
  73. Robertson M, Laraque F, Mavronicolas H, et al. Linkage and retention in care and the time to HIV viral suppression and viral rebound–New York City. AIDS Care. 2015;27:260–267. https://doi.org/10.1080/09540121.2014.959463
  74. Ceccherini-Silberstein F, Cozzi Lepri A, Alteri C, et al. Pre-ART HIV-1 DNA in CD4+ T cells correlates with baseline viro-immunological status and outcome in patients under first-line ART. J Antimicrob Chemother. 2018;73:3460–3470. https://doi.org/10.1093/jac/dky350
  75. Joseph Davey D, Abrahams Z, Feinberg M, et al. Factors associated with recent unsuppressed viral load in HIV-1-infected patients in care on first-line antiretroviral therapy in South Africa. Int J STD AIDS. 2018;29:603–610. https://doi.org/10.1177/0956462417748859
  76. Adams JW, Marshall BD, Salleh NAM, et al. Receipt of opioid agonist treatment halves the risk of HIV-1 RNA viral load rebound through improved ART adherence for HIV-infected women who use illicit drugs. Drug Alcohol Depend. 2020;206:107670. https://doi.org/10.1016/j.drugalcdep.2019.107670
  77. Dhairyawan R, Okhai H, Hill T, et al. Differences in HIV clinical outcomes amongst heterosexuals in the United Kingdom by ethnicity. AIDS. 2021;35:1813–1821. https://doi.org/10.1097/QAD.0000000000002942


Crossref Citations

No related citations found.