Abstract
Background
Human Immuno-Deficiency Virus (HIV) remains one of the world’s significant public health challenges. Viral suppression is the key indicator for treatment success in People living with HIV (PLHIV). We determined the level of viral suppression, and its associated factors among PLHIV attending Federal Medical Centre Katsina (FMC Katsina), Nigeria.
Methods
This retrospective descriptive cross-sectional study was conducted on 913 HIV positive adults enrolled in care between January 2009 and December 2019. Information on socio-demographics, clinical, immunological, Viral load (VL), and other relevant parameters were extracted from the patients’ care records. The primary outcome was the proportion of patients that achieved viral suppression. We also analyzed variables that were associated with VL suppression.
Results
Of 913, records of 831 (91.0%) registered patients were analyzed. During the period, 751 (90.4%) achieved viral suppression, 427 (51.4%) had CD4 counts ≥ 500 and 477 (57.4%) were on HAART for ≥ 5 years. Majority, 793 (95.4%) were on first-line HAART regimen (Tenofovir-Lamivudine-Dolutegravir or Abacavir-Lamivudine-Dolutegravir), and 809 (97.4%) in the non-advanced stage (WHO stages 1 and 2). The median (interquartile range) of viral load was 20 (20–40) vs 19,989 (3311–110,340) cp/ml in virally suppressed, and unsuppressed respectively. Factors associated with viral suppression included being unemployed (Adjusted OR [AOR] 4.9, 95% CI 2.771, 8.539), educated (AOR 4.2, 95% CI 1.098, 16.223), having a baseline CD4 count ≥ 500 cells/µl (AOR 2.7, 95% CI 1.588, 4.625), and being on first line HAART regimen [AOR 7.0, 95% CI 3.220, 15.648].
Conclusions
Our study demonstrated a good viral suppression among PLHIV on HAART. Variables associated with viral suppression included unemployment, formal education, high baseline CD4 count, and first line HAART regimen.
Keywords: Viral suppression, HIV-Positives, Antiretroviral Therapy, Nigeria
Background
Human Immuno-Deficiency Virus (HIV) is a leading cause of infections worldwide despite the success of highly active antiretroviral therapy (HAART) [1]. It remains one of the world’s most significant public health challenges, affecting about 38 million of the world’s population majority of whom are living in low and middle income countries [2]. Nigeria shares a portion of this estimate with a recent national prevalence of 1.4%. With varying prevalence across the country, Katsina state has the lowest prevalence of 0.3% while Akwa-Ibom state has the highest prevalence of 5.6% [3, 4].
The 90-90-90 target by UNAIDS envisages that by 2020, 90% of PLHIV will know their HIV status, 90% of people who know their HIV-positive status will be accessing treatment and 90% of people on treatment will have suppressed viral loads [5]. However, in 2018 Nigeria has only 67% of PLHIV that knew their status, of which 53% were on treatment and only 42% were virally suppressed [5]. The northwest zone of Nigeria also reflects similar statistics as only 9 out of 20 PLHIV on HAART achieved viral suppression [5, 6].
Viral load (VL) measurement is the gold standard for monitoring treatment success. PLHIV on HAART with unsuppressed viral load have a higher risk of disease progression, transmission, and mortality [7]. Available statistics have shown that Nigeria is far behind the target of 'UNAIDS 90-90-90 aspirations’ despite the recent downward trend in prevalence and incidence. Within the limits of our literature search on major databases- PubMed, Medline, Scopus, Google scholars, and Web of Science-there was no research that has evaluated viral suppression among HIV patients in the north-western part of Nigeria.
The objective of this study was to determine the level of viral suppression and its associated factors among HIV positive adults attending the HIV clinic at FMC Katsina, Nigeria.
Methods
This retrospective cross-sectional descriptive study was conducted from January 2009 to December 2019 at FMC, Katsina. The hospital is a 1000 bed capacity, tertiary health facility. It serves as a referral center for both private and other public health facilities in the state, neighboring states, and the Niger Republic. The HIV clinic otherwise referred to as Action Aid clinic was established in 2006 and provides services for the diagnosis, treatment, and prevention of HIV, inclusive of free counseling and testing. It can accommodate about two hundred patients per clinic day and further subdivided into units. The HIV clinic units included the adult ART clinic, Paediatrics ART unit, the Prevention of Mother-to-Child Transmission (PMTCT) unit, HIV/TB co-infection unit, Pharmacy unit and the laboratory.
Study participants and data collection
The source of data was from the database of the HIV clinic obtained from all PLHIV enrolled in ART care from January 2009 to December 2019 at FMC Katsina. A total of 1034 clients were registered within this period. The database provided information on socio-demographics, clinical, immunological, virological and other relevant parameters of patients. A total number of 913 adult clients were enrolled within the study period and they were all considered as the study subjects. We excluded children and adolescents less than 18 years on HAART. We used VL testing data for samples corresponding to HIV positive patients who had been on HAART for at least 6 months. Where there were more than one VL results, the most recent (not more than 12 months prior in line with the country’s national guideline for HIV) was used for the data. We abstracted data on VL testing results (for plasma) measured in terms of viral RNA copies/ml of blood. Before 2017, virological monitoring was carried out only in those with clinical suspicion of failure or poor adherence. Following policy change in the country and update of National guideline in 2018, all enrolled patients among the PLHIV had a minimum of yearly viral load monitoring. However, where the viral load was above the thresholds of 1000 copies/ml, intensified adherence counseling were carried out and viral load assays repeated within three to 6 months.
Outcome measures
The primary outcome was virological suppression, defined as having ≤ 1000 copies of viral RNA/ml of blood for plasma, as provided by the National guideline for treatment and control of HIV/AIDS 2018. The secondary outcome of this study was factors associated with viral suppression.
Definition of terms
Base line CD4 count: This was the CD4 count at the commencement of HAART.
Body mass index (BMI): The body mass index was determined by dividing the weight in kilogram with height in metre squared and classified using Centres for Disease Control (CDC) into underweight (< 18.5 kg/m2), normal or healthy weight (18.5 to 24.9 kg/m2), overweight (25 to 29.9 kg/m2) and obese (≥ 30 kg/m2).
TB status: This was defined as confirmation or diagnosis of Mycobacterium tuberculosis during the study past 1 year.
Laboratory testing methods
The laboratory analysis was carried out by the CDC accredited laboratory of the Aminu Kano Teaching Hospital, Kano. For each sample collected from the patients, RNA was extracted and plasma VL determined using Polymerase chain reaction (PCR). The VL measurements were carried-out in 2018 and 2019.
Data quality assurance
One of the authors extracted the data into Microsoft Excel spreadsheet and this was verified independently by two other co-authors to ensure accuracy and consistency of the data.
Data analysis
This was done using Epi-info version 7 and IBM SPSS statistics for Windows, version 25 (IBM Corp. Armonk, NY, USA). The proportion of subjects with virological suppression was expressed as percent. We compared the socio-demograhics (age, sex, educational status, marital status, employment, and occupation), BMI categories and distance from the health facility using chi-square and Fischer’s exact test where apporiate between the subjects that were virally suppressed and those without viral suppression. Besides, clinical and laboratory parameters (baseline CD4 count, duration on HAART, HAART regimen, WHO staging of HIV, and pregnancy status) were also compared between those that were virologically suppressed and unsuppressed subjects using Chi-square and Fischer’s exact test as appropriate. The viral loads were summarized as median with interquartile range (IQR) and compared using Man-Whitney U test between the two groups. Based on the literature, some variables (age, and gender) along with other variables (occupation, educational status, BMI categories, baseline CD4 count, duration on HAART, HAART regimens) with p-value less than 0.25 on the bivariate analysis were entered into binary logistic regression model to determine factors that were associated with virological suppression. The p-value for level of statistical significance was set at < 0.05.
Results
During the study period, a total of 1034 subjects including children were enrolled into care at the centre. Out of the 1034 registered subjects, 913 (88.3%) were adults. Of the 913 adults, we excluded 82 subjects (35 had missing biodata, 27 had no traceable viral loads in the past 12 months, while the records of 20 showed non active status -no clinic visit and could not be traced in the past 1 year). Thus, we included 831 (91.0%) in the final data analysis as highlighted in Fig. 1.
Fig. 1.
Flow chart of the study subjects. ART-Antiretroviral therapy; *all the subjects are on ART
The subjects age ranged from 18 to 77 years. The mean age (standard deviation) of the subjects was 34.5 ± 9.3 years. Most of the subjects were below the age of 50 years (782; 94.1%). There were more females, 578 (69.6%) than males. A total of 709 (85.3%) were unemployed while 78.6% were married as shown in Table 1.
Table 1.
Socio-demographic profile of the study participants (n = 831)
| Variables | Frequency (n) | Percentage (%) |
|---|---|---|
| Current age (years) | ||
| 18–27 | 56 | 6.7 |
| 28–37 | 295 | 35.5 |
| 38–47 | 305 | 36.7 |
| 48–57 | 138 | 16.6 |
| 58–67 | 34 | 4.1 |
| 68–77 | 2 | 0.2 |
| ≥ 78 | 1 | 0.1 |
| Gender | ||
| Male | 253 | 30.4 |
| Female | 578 | 69.6 |
| Occupation | ||
| Business | 7 | 0.8 |
| Employed | 114 | 13.7 |
| Retired | 1 | 0.12 |
| Unemployed | 709 | 85.3 |
| Marital status | ||
| Divorced | 56 | 6.7 |
| Married | 653 | 78.6 |
| Single | 56 | 6.7 |
| Widowed | 66 | 7.9 |
| Educational status | ||
| Qur'anic | 12 | 1.4 |
| Primary | 163 | 19.6 |
| Secondary | 536 | 64.5 |
| Tertiary | 104 | 12.5 |
| None | 16 | 1.9 |
| Location | ||
| Far from aFMCK (≥ 100 km) | 63 | 7.6 |
| Near from FMCK (< 100 km) | 768 | 92.4 |
aFMCK-Federal Medical Centre, Katsina
The median viral load was 20 (20–74) cp/ml in the study subjects. The median viral load in those that achieved viral suppression range from 20 to 925 cp/ml, while in those without viral suppression, VL range from 1170 to 2,468,443.0). In 2018, out of 87 subjects, 77 (88.5%) had viral suppression. Similarly, in 2019, out of 774 subjects, 704 (91.0%) had achieved viral suppression. The duration on HAART, TB status, WHO staging of the disease, and pregnancy status were not related to viral suppression. However, baseline CD4 count and HAART regimens were associated with viral suppression (Table 2).
Table 2.
Factors associated with viral suppression (n = 831)
| Variables | n (%) | Viral load suppressed n = 751 | Viral load unsuppressed n = 80 | P value |
|---|---|---|---|---|
| Baseline CD4 counts (cells/µl) * | ||||
| < 500 | 404 (48.6) | 346 (46.1) | 58 (72.5) | < 0.001 |
| ≥ 500 | 427 (51.4) | 405 (53.9) | 22 (27.5) | |
| Years on HAART | ||||
| < 5 years | 354 (42.6) | 325 (43.3) | 29 (36.3) | 0.237 |
| ≥ 5 years | 477 (57.4) | 426 (56.7) | 51 (63.7) | |
| HAART Regimen | ||||
| First Line | 793 (95.4) | 728 (96.9) | 65 (81.3) | < 0.001 |
| Second Line | 38 (4.6) | 23 (3.1) | 15 (18.7) | |
| TB confirmed** | ||||
| Yes | 21 (2.5) | 19 (2.8) | 2 (2.8) | 1.000f |
| No | 731 (88.0) | 662 (97.2) | 69 (97.2) | |
| Missing | 79 (9.5) | |||
| Disease stage | ||||
| WHO stages 1 and 2 | 809 (97.4) | 732 (97.5) | 77 (96.3) | 0.461f |
| WHO stages 3 and 4 | 22 (2.6) | 19 (2.5) | 3 (3.7) | |
| Pregnancy Status (n = 578) | ||||
| Not Pregnant | 558 (96.5) | 501 (96.7) | 57 (95.0) | 0.452f |
| Pregnant | 20 (3.5) | 17 (3.3) | 3 (5.0) | |
|
Viral Load (cp/ml) Median (IQR) |
20 (20–74) Range (20 to 2,469,613) |
20 (20–40) Range (20 to 925) |
19,989 (3311 to 110,340) Range (1170 to 2,468,443.0) |
< 0.001 |
|
2019 Viral Load (cp/ml) Median (IQR) |
20 (20–70.5) Range (20 to 2,469,613) N = 744 |
20 (20–40) Range (20 to 845) N = 674 |
17,086.5 (3228.8–131,695 Range (1170 to 2,469,613) N = 70 |
< 0.001 |
|
2018 Viral Load (cp/ml) Median (IQR) |
20 (20–119) Range (20 to 112,454) N = 87 |
20 (20–39.5) Range (20 to 925) N = 77 |
31,997.0 (4205.5–68,372.0) Range (1373 to 112,454) N = 10 |
< 0.001 |
*Baseline value of CD4 count at enrollment (Prior to the commencement of anti-retroviral therapy-ART); **TB confirmed cases among those with viral load suppression; IQR-Interquartile range; f-Fischer exact test
Tables 3 and 4 show the logistic regression analysis of factors that were associated with VL suppression. The age group and sex were not associated with viral load suppression. However, unemployed subjects had a significant association with viral suppression compared with employed subjects (Adjusted odds ratio [AOR] 4.86, 95% confidence interval 2.771 to 8.539). Similarly, subjects with formal education had a significant viral suppression compared with those without formal education(AOR 4.221, 95% CI 1.098, 16.223). A baseline CD4 count of 500 cells/µl or more was significantly associated with viral suppression (AOR 2.71, 95% CI 1.588, 4.625). Subjects on first line HAARTS also had significant viral suppression when compared with those on second line (7.208, 95% CI 3.220, 15.648).
Table 3.
Unadjusted and adjusted binary logistic regression analysis of factors associated with Viral load suppression
| Variables | Viral loads | Unadjusted | Adjusted | |||||
|---|---|---|---|---|---|---|---|---|
| Suppressed (n = 751, %) | Unsuppressed (n = 80, %) | OR | 95% CI | p | OR | 95% CI | P | |
| Agea | ||||||||
| 18 to 35 | 258 (34.4) | 29 (36.3) | 1 | 0.606, 1.777 | 0.133 | 1 | 0.583, 1.906 | 0.861 |
| 36 to 45 | 277(36.9) | 30 (37.5) | 1.038 | 1.054 | ||||
| 46 and older | 216 (28.8) | 21 (26.3) | 1.156 | 0.641, 2.086 | 0.207 | 1.116 | 0.534, 2.332 | 0.771 |
| Gender | ||||||||
| Male | 233 (31.0) | 20 (25.0) | 1 | 0.437, 1.258 | 0.267 | 1 | 0.358, 1.325 | 0.264 |
| Female | 518 (69.0) | 60 (75.0) | 0.741 | 0.689 | ||||
| Occupation | ||||||||
| Employed | 91 (12.1) | 30 (37.5) | 1 | 2.632, 7.196 | < 0.001 | 1 | 2.771, 8.539 | < 0.001 |
| Unemployed | 660 (87.9) | 50 (62.5) | 4.352 | 4.864 | ||||
| Educational status | ||||||||
| No formal education | 13 (1.7) | 3 (3.8) | 1 | 0.617, 7.932 | 0.223 | 1 | 1.098, 16.223 | 0.036 |
| Formal education | 738 (98.3) | 77 (96.3) | 2.212 | 4.221 | ||||
| Marital status | ||||||||
| Unmarried | 159 (21.2) | 19 (23.8) | 1 | 0.673, 1.998 | 0.593 | – | – | – |
| Married | 592 (78.8) | 61 (76.3) | 1.160 | |||||
| BMI categories ≠ | ||||||||
| 18.5 to 24.9 | 289 (38.5) | 39 (48.8) | 1 | 1.032, 3.969 | 0.040 | 1.839 | 0.908, 3.726 | 0.091 |
| < 18.5 | 180 (24.0) | 12 (15.0) | 2.024 | |||||
| 25 to 29.9 | 197 (26.2) | 20 (25.0) | 1.329 | 0.753, 2.347 | 0.327 | 1.385 | 0.748, 2.565 | 0.300 |
| 30 and above | 85 (11.3) | 9 (11.3) | 1.275 | 0.594, 2.736 | 0.534 | 1.283 | 0.565, 2.917 | 0.551 |
| Locationc | ||||||||
| < 100 km | 692 (92.1) | 76 (95.0) | 1 | 0.573, 4.583 | 0.363 | – | – | – |
| ≥ 100 km | 59 (7.9) | 4 (5.0) | 1.620 | |||||
Variables included in the adjusted odds ratio were age, sex, occupation, educational status, BMI categories, baseline CD4 count, duration on HAART, and HAART regimens
aAge at the commencement of Anti-retroviral therapy; HAART-Highly active anti-retroviral therapy, Reg-regimen; BMI-Body mass index; CDC classification≠. cLocation of participants from FMC Katsina
Table 4.
Binary logistic regression analysis of factors associated with Viral load suppression
| Variables | Viral load | Unadjusted | Adjusted | |||||
|---|---|---|---|---|---|---|---|---|
| Suppressed (n = 751, %) | Unsuppressed (80, %) | OR | 95% CI | p | OR | 95% CI | p | |
| Baseline CD4 (cells/µl) | ||||||||
| < 500 | 346 (46.1) | 58 (72.5) | 1 | 1.851, 5.146 | < 0.001 | 1 | 1.588, 4.625 | < 0.001 |
| ≥ 500 | 405 (53.9) | 22 (27.5) | 3.086 | 2.710 | ||||
| Years on HAART | ||||||||
| < 5 | 325 (43.3) | 29 (36.3) | 1 | 0.462, 1.202 | 0.228 | 1 | 0.686. 2.019 | 0.555 |
| ≥ 5 | 405 (56.7) | 51 (63.7) | 0.745 | 1.117 | ||||
| HAART regimen | ||||||||
| Second line | 23 (3.1) | 15 (18.8) | 1 | 3.634, 14.683 | < 0.001 | 1 | 3.220,15.648 | < 0.001 |
| First line | 728 (96.9) | 65 (81.3) | 7.304 | 7.208 | ||||
| Disease stage | ||||||||
| WHO stage 1 & 2 | 732 (97.5) | 77 (96.3) | 1 | 0.193, 2.302 | 0.521 | – | – | – |
| WHO stage 3 & 4 | 19 (2.5) | 3 (3.8) | 0.666 | |||||
| Pregnancy status | ||||||||
| Pregnant (20) | 17 (3.3) | 3 (5.0) | 1 | 0.441, 5.455 | 0.494 | – | – | – |
| Not pregnant (558) | 501 (96.7) | 57 (95.0) | 1.551 | |||||
Variables included in the adjusted odds ratio were age, sex, occupation, educational status, BMI categories, baseline CD4 count, duration on HAART, and HAART regimens
HAART-Highly active anti-retroviral therapy
Discussion
The level of viral suppression in this study was high and it falls within the global target of 90% viral suppression among PLHIV on HAART by USAID [5]. This study also showed that the level of viral suppression in this cohort was one of the highest levels of viral suppression in low-middle income countries. This level is higher compared with the national level of viral suppression of 44.4% in the north-western part of Nigeria [6]. The value of viral suppression in this study was also higher compared to 79% reported in a multi-center Nigerian study [8], and 84% in Borno state, north-eastern Nigeria [9], 69% in Ghana [10] and 73% in northern Ethiopia [11]. High level of viral suppression in this study are comparable with the reports from Uganda where a level of 95% was observed for viral suppression after 12 months of HAART among PLHIV [12]. Similarly, the level of viral non-suppression obtained in this study is comparable to 9.0% and 7.0% reported in the African cohort study [13], and Vietnam [14] respectively. The high levels of viral suppression observed in this study compared to the other studies may be due to several reasons such as; the cut off value used for VL suppression in this study was VL < 1000 compared with a low value of 400 used in the earlier Nigerian studies that evaluated viral suppression after test and treat protocols [8] and after 6 months of initiation of first-line of HAART in a Moroccan study [15]. Furthermore, our centre is a tertiary health care centre with a dedicated unit for PLHIV and patients routinely undergo adherence counselling during their clinic visits which could have enhanced their compliance with their medications leading to viral suppression [16]. Our findings also suggest that the goal of achieving a 90% level of viral suppression is achievable in a resource-limited country like ours and the current approach in the management of HIV should be sustained.
This study also identified factors associated with viral suppression as having high baseline CD4 counts, being unemployed, being educated and being on first-line HAART. The study in Ethiopia reported a low baseline CD4 count and 2nd line HAART regimen to be associated with poor viral load suppression [11]. In contrast, the study in Borno State, north-eastern Nigeria found younger age group and marital status to be associated with poor viral suppression [9]. A South African study also identified low CD4 count to be associated with poor viral load suppression [17]. The CD4 cells are one of the prime targets of HIV, hence it’s fall corresponds to increasing viral loads. Although not the main marker of monitoring HIV, low CD4 counts at the beginning of treatment calls for closer monitoring of the PLHIV as they have a higher chance of having poor viral suppression.
Our study identified that being on the firstline line HAART was associated with good viral suppression when compared with those on the second-line. This is consistent with the observation in Borno State, northeast Nigeria where being on the second line HAARTs was associated with high viral load counts [9]. The African cohort study also found being on the second line HAART as predictive of viral suppression [13]. The higher level of non viral suppression among those on the second line HAART may indicate a high level of resistance as patients are moved to second-line following the failure of first-line. This is also a source of concern as non-viral suppression on second-line may necessitate a consideration for the commencement of third-line HAART which are presently not very available in resource limited countries like Nigeria. Besides, unemployed have higher odds of viral suppression with an AOR of 4.8. A study in Ghana that included occupations among factors that may predict non-suppression of viral load, did not observe any significant relationship [10]. Several factors may account for a higher level of suppression of viral load among the employed people in this study. The work schedules may affect their compliance and adherence levels. Also, those that work in the formal sectors may not be regular at clinic follow up due to their work schedules and the need for frequent permission for clinic attendance. Our study also showed that baseline CD4 counts greater or equal to 500 have higher odd of suppression of viral loads. Similarly, a study in Ethiopia also observed low CD4 count to be predictive of viral load non-suppression [18]. In Vietnam, low CD4 counts were also found to be predictive of non-viral suppression [14]. The findings of low baseline CD4 counts being associated with viral load non-suppression affirms the previous observation that patients with high viral loads tend to have low CD4 counts and suggests a slow viral clearance.
The strength of our study included the large number of subjects that had at least one viral load in the preceding 12 months. However, our study is limited being a retrospective study, as only few subjects had their viral load monitored before 2018. We also excluded few subjects (82) due to missing information. Although we compared with global set target of 90-90-90, the samples were not randomly drawn. Hence, our findings may not be generalizable. Furthermore, being a retrospective study, we could not adjust for some potential confounders, which may have affected our findings.
Conclusion
Our study demonstrates a low level of viral non-suppression among PLHIV on HAART and the target of 90% viral suppression in the PLHIV on HAART by the USAID is achievable in resource constraint settings. Also, having a high baseline CD4 count, being employed, uneducated and being on first-line HAART are predictive of viral load suppression.
Acknowledgements
We wish to acknowledged Usman Umar Turaji and the entire staff of HIV-Clinic, FMC Katsina and the IHVN Nigeria.
Abbreviations
- AIDS
Acquired Immune Deficiency Syndrome
- AOR
Adjusted Odds Ratio
- ART
Antiretroviral therapy
- CD-4
Cluster of Differentiation 4
- CDC
Centers for Disease Control and Prevention
- CI
Confidence Interval
- OR
Odds Ratio
- HIV
Human Immunodeficiency Virus
- PEPFAR
President’s Emergency Plan For AIDS Relief
- PLHIV
People Living With HIV/AIDS
- P-value
Probability value
- UNAIDS
United Nations Programme on HIV and AIDS
- VL
Viral Load
- WHO
World Health Organization
- FMC Katsina
Federal Medical Centre, Katsina
Authors' contributions
SBA conceptualized and designed the study, involved in data analyses, acquisition of data, tabulating the data, interpretation of data, preparing tables and figures, drafting the initial manuscript and critically revising the manuscript. ORI has involved in interpretation of data, drafting the initial manuscript, and critically revising the manuscript. ABO, RIY, IB, SH, SAI, OTIA, SBM, MY and MKA have contributed in interpretation of the data, initial draft synthesis, and revising the manuscript. MKA and MBS have primary responsibility for final content and involved in final review. All authors read and approved the final manuscript.
Funding
There was no fund for this study.
Availability of data and materials
The data that support the findings of this study are available from the Federal Medical Centre, Katsina HIV clinic. In the event that someone wants to request for the data for this study, he/she should seek permission from the Medical Director, Federal Medical Centre, Katsina in person of Dr SULEIMAN, Bello Muhammad (mbskt@yahoo.co.uk).
Declarations
Ethics approval and consent to participate
Ethical clearance and approval were obtained from Federal Medical Centre, Katsina Health Research Ethical Review Committee. Permission to use the data was obtained from the Federal Medical Centre, Katsina management. The data were from a secondary database on HIV infected patients for VL monitoring while on treatment. The data were not accessible by any other third party other than the study team.
Consent for publication
Not applicable.
Competing interests
Authors’ declare that there are no competing interests.
Footnotes
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- 1.The Global Burden of Disease study (GBD 2015)_HIV collaborators. Estimate of global, regional, and national incidence, prevalence and mortality of HIV, 1980–2015: the global burden of disease study 2015. Lancet HIV 2016:3(8):e361–87. 10.1016/s2352-3018(16)30087-x. Accessed 22 Jan 2020. [DOI] [PMC free article] [PubMed]
- 2.World Health Organization. HIV/AIDS Fact File. https://www.who.int/news-room/fact-sheets/detail/hiv-aids. https://origins.who.int/features/factfiles/hiv/en. Accessed 1 Nov 2020.
- 3.UNAIDS Press Release Abuja/Geneva 14th March 2019. https://www.unaids.org/en/resources/presscentre/pressreleaseandstatentarchive/2019/march/20190314_nigeria. Accessed 22 Jan 2020.
- 4.National Agency for the Control of AIDS (NACA). Nigeria HIV Prevalence Rate. https://naca.gov.ng/nigeria-prevalence-rate/. Accessed 22 Jan 2020.
- 5.UNAIDS. The 90–90–90 Ambitious Treatment Target to Help End AIDS Epidemic. http://www.unaids.org/en/resources/documents/2014/90-90-90. Accessed 22 Jan 2020]
- 6.National Agency for the Control of AIDS (NACA). Nigeria HIV/AIDS Indicator and Impact Survey March 2019. Available at https://naca.gov.ng/wp-content/uploads/2019/03/NAIIS-Northwest. Accessed 22 Jan 2020.
- 7.World Health Organization. What’s New in Treatment Monitoring: Viral Load and CD4 Testing. WHO-HIV-2017 Update July 2017. https://apps.who.int/iris/bitstream/handle/10665/235891/WHO-HIV-2017.22-eng. Accessed 20 Jan 2020.
- 8.Stafford KA, Odafe SF, Lo J, Ibrahim R, Ehoche A, Niyang M, et al. Evaluation of the clinical outcomes of the Test and Treat strategy to implement Treat All in Nigeria: results from the Nigeria Multi-Center ART Study. PLoS ONE. 2019;14:1–20. doi: 10.1371/journal.pone.0218555. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Sunkanmi F, Paul Y, Peter D, Nsikan A, Joseph J, Opada E, et al. Factors influencing viral load non-suppression among people living with HIV (PLHIV) in Borno State, Nigeria: a case of Umaru Shehu Ultra-Modern Hospital. J Adv Med Res. 2020;32:98–105. doi: 10.9734/jammr/2020/v32i330388. [DOI] [Google Scholar]
- 10.Ofori-Attah P, Ameke LS, Obirikorang C, Orish VN, Kpene GE, Agboli E, et al.Viral suppression and its associated factors in hiv patients on highly active antiretroviral therapy (HAART): a retrospective study in the Ho Municipality, Ghana. AIDS Res Treat. 2020; 1–7.
- 11.Desta AA, Tewolde WW, Futwi N, Gebrecherkos TG, Goyitom GG, Asfawosen AB, et al. HIV virological non-suppression and factors associated with non-suppression among adolescents and adults on antiretroviral therapy in northern Ethiopia: a retrospective study. BMC Infect Dis. 2020;20:1–10. doi: 10.1186/s12879-019-4732-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Ssemwanga D, Asio J, Watera C, Nannyonjo M, Nassolo F, Lunkuse S, et al. Prevalence of viral load suppression, predictors of virological failure and patterns of HIV drug resistance after 12 and 48 months on first-line antiretroviral therapy: a national cross-sectional survey in Uganda. J Antimicrob Chemother. 2020;75(5):1280–1289. doi: 10.1093/jac/dkz561. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Kiweewa F, Esber A, Musingye E, Reed D, Crowell TA, Cham F, et al. HIV virologic failure and its predictors among HIV-infected adults on antiretroviral therapy in the African Cohort Study. PLoS One. 2019;14:1–16. doi: 10.1371/journal.pone.0211344. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Rangarajan S, Donn JC, Giang LT, Bui DD, Nguyen HH, Tou PB, et al. Factors associated with HIV viral load suppression on antiretroviral therapy in Vietnam. J Virus Era. 2016;2(2):94–101. doi: 10.1016/S2055-6640(20)30466-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Abebe G, Bonsa Z, Kebede W. Treatment outcomes and associated factors in tuberculosis patients at Jimma University Medical Center: a 5-year retrospective study Gemeda. Int J Mycobacteriology. 2017;6:239–245. doi: 10.4103/ijmy.ijmy_87_17. [DOI] [PubMed] [Google Scholar]
- 16.Mainaa EK, Mureithia H, Adana AA, Muriukib J, Lwembeb RM, Bukusi EA. 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. doi: 10.1016/j.ijid.2020.05.097. [DOI] [PubMed] [Google Scholar]
- 17.Govender S, Otwombe K, Essien T, Panchia R, de Bruyn G, Mohapi L, et al. CD4 counts and viral loads of newly diagnosed hiv-infected individuals: implications for treatment as prevention. PLoS ONE. 2014;9(3):e90754. doi: 10.1371/journal.pone.0090754. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Bayu B, Tariku A, Bulti AB, Habitu YA, Derso T, Teshome DF. Determinants of virological failure among patients on highly active antiretroviral therapy in University of Gondar Referral Hospital, Northwest Ethiopia: a case-control study. HIV/AIDS Res Palliat Care. 2017;8(9):153–159. doi: 10.2147/HIV.S139516. [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.
Data Availability Statement
The data that support the findings of this study are available from the Federal Medical Centre, Katsina HIV clinic. In the event that someone wants to request for the data for this study, he/she should seek permission from the Medical Director, Federal Medical Centre, Katsina in person of Dr SULEIMAN, Bello Muhammad (mbskt@yahoo.co.uk).