The Frequency and Predictors of Unsuppressed HIV Viral Load Among People with HIV in Nyaruguru District, Rwanda

Abstract

Background By the end of 2015, epidemiological studies approximated 37 million people living with HIV (PLHIV) and 46.3% of them were initiated to antiretroviral therapies. From the 90-90-90 strategy, by 2020 at global level, 90% of all people living with HIV were expected to suppress viral load (VL). Although VL suppression is an important indicator of treatment success in PLHIV, studies on this indicator remain scarce in Rwanda where the prevalence of HIV is 3% with 9% for non-suppression. This work, thus, determined the prevalence of VL non-suppression and its associated predictors among PLHIV. Methods A cross-sectional study was conducted among 637 PLHIV enrolled in healthcare services between 2016 and 2017 in Nyaruguru district. Socio-demographic, treatment, clinical, immunological and VL data were extracted from medical records. Bivariate and multivariate logistic regression analyses were performed to determine associated factors with VL suppression considering 95% confidence intervals and statistical significance of p<0.005. Results More than half of participants were female (57.77%). The prevalence of unsuppressed HIV VL was 8.9% and 88.7% of respondents were satisfied with the service provided. Males were more likely to be unsuppressed HIV VL [aOR = 3.02; 95% CI (1.19–7.64), p = 0.02] than females. Higher likelihoods of VL non-suppression were among those with history of clinical failure [aOR = 3.14; 95% CI (1.70–14.03), p = 0.034] or history of treatment interruption [aOR = 8.29; 95% CI (2.60–26.42) p = 0.002]. Those with a bad perception toward the whole life treatment were more likely to be unsuppressed [aOR = 4.32; 95% CI (1.98–18.99), p = 0.049] than their counterparts. Conclusion Sex, treatment interruption, bad perception toward the whole life treatment, clinical failure and lack of confidentiality were the major predictors of being unsuppressed. More efforts on counseling HIV patients to improve their knowledge would drop levels of VL non-suppression, so improving the quality of service should be prioritized to increase suppression.

Prevalence and factors associated with viral non‐suppression in people living with HIV receiving antiretroviral therapy in sub‐Saharan Africa: A systematic review and meta‐analysis

“…The collective evidence from various studies 27,31,32,34,35,47,49 revealed a statistically significant association between male gender and an increased likelihood of experiencing VNS (AOR: >1, p ‐value <0.05) in the context of HIV. Younger age often exhibits a higher susceptibility to experiencing VNS 10,27,30,49,50 (AOR: >1, 95%, CI: <1 or >1, p ‐value <0.05).…”

“…Of the included studies, 15 were cross-sectional, 10 were cohort, five were nested studies in clinical trials and two were case-control (Table 1). The majority (29/32) of the studies 10,22,23,[25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40][41][42][43][45][46][47][49][50][51][52] used a viral load threshold of ≥1000 copies/mL to define VNS.…”

Predictors of Interruptions in Antiretroviral Therapy among People Living with HIV in Nigeria: A Retrospective Cohort Study Using the Nigeria National Data Repository

“…Logistic regression captured some predictors of IIT, including female sex. In the 2019 study by Aliyu et al[17] 2021 study by Tomescu et al[16], the 2022 study by Hakizayezu et al[13], and a 2020 study by Abebe et al[20] sex was found to be predictive of interruptions in care; however, in all of these studies, the men were at a higher risk of interruption or its proxy such as loss to follow up. Our findings may differ from those of prior studies because we were restricted to those who interrupted but re-engaged in care.…”

“…People living outside of state capitals, the federal capital territory, and Lagos State were more likely to experience at least one interruption event. The Hakizayezu et al study identified other predictors, including a prior history of treatment interruption (which we could not explore as were looking at first interruption) and good perception toward the whole-of-life treatment[13]. Aliyu et al identified additional predictors including HIV viral load indication and result as well as age[17] (which was not predictive in this study or in the Tomescu et al study[16]), and regimen at the start of ART.…”

“…Prior studies have been carried out to understand the predictors of IIT and loss to follow-up (LTFU) in not just Nigeria, but in other sub-Saharan countries, including Mali, Ethiopia, and Rwanda, and have identified different sets of predictors including age, baseline CD4 count, sex, marital status, education, access to care, treatment regimens, and treatment fatigue to mention a few [11], [12], [13], [14], [15], [16], [17]. Most of the evidence generated from Nigeria has been based on cohorts from groups of health facilities supported by individual organizations that may employ specific models of care and can also limit geographic representation.…”