In December 2016, the Nigerian Federal Ministry of Health updated its HIV guidelines to a Treat All approach, expanding antiretroviral therapy (ART) eligibility to all individuals with HIV infection, ...regardless of CD4+ cell count, and recommending ART be initiated within two weeks of HIV diagnosis (i.e., the Test and Treat strategy). The Test and Treat policy was first piloted in 32 local government areas (LGAs). The primary objective of this study was to evaluate the clinical outcomes of adult patients initiated on ART within two weeks of HIV diagnosis during this pilot. We conducted a retrospective cohort analysis of patients who initiated ART within two weeks of new HIV diagnosis between October 2015 and September 2016 in eight randomly selected LGAs participating in the Test and Treat pilot study. 2,652 adults were newly diagnosed and initiated on ART within two weeks of HIV diagnosis. Of these patients, 8% had documentation of a 12-month viral load measurement, and 13% had documentation of a six-month viral load measurement. Among Test and Treat patients with a documented viral load, 79% were suppressed (≤400 copies/ml) at six months and 78% were suppressed at 12 months. By 12 months post-ART initiation, 34% of the patients who initiated ART under the Test and Treat strategy were lost to follow-up. The median CD4 cell count among patients initiating ART within two weeks of HIV diagnosis was 323 cells/mm3 (interquartile range, 161-518). While randomized controlled trials have demonstrated that Test and Treat strategies can improve patient retention and increase viral suppression compared to standard of care, these findings indicate that the effectiveness of Test and Treat in some settings may be far lower than the efficacy demonstrated in randomized controlled trials. Significant attention to the way Test and Treat strategies are implemented, monitored, and improved particularly related to early retention, can help expand access to ART for all patients.
The Nigerian Antiretroviral therapy (ART) program started in 2004 and now ranks among the largest in Africa. However, nationally representative data on outcomes have not been reported.
We evaluated ...retrospective cohort data from a nationally representative sample of adults aged ≥15 years who initiated ART during 2004 to 2012. Data were abstracted from 3,496 patient records at 35 sites selected using probability-proportional-to-size (PPS) sampling. Analyses were weighted and controlled for the complex survey design. The main outcome measures were mortality, loss to follow-up (LTFU), and retention (the proportion alive and on ART). Potential predictors of attrition were assessed using competing risk regression models.
At ART initiation, 66.4 percent (%) were females, median age was 33 years, median weight 56 kg, median CD4 count 161 cells/mm3, and 47.1% had stage III/IV disease. The percentage of patients retained at 12, 24, 36 and 48 months was 81.2%, 74.4%, 67.2%, and 61.7%, respectively. Over 10,088 person-years of ART, mortality, LTFU, and overall attrition (mortality, LTFU, and treatment stop) rates were 1.1 (95% confidence interval (CI): 0.7-1.8), 12.3 (95%CI: 8.9-17.0), and 13.9 (95% CI: 10.4-18.5) per 100 person-years (py) respectively. Highest attrition rates of 55.4/100py were witnessed in the first 3 months on ART. Predictors of LTFU included: lower-than-secondary level education (reference: Tertiary), care in North-East and South-South regions (reference: North-Central), presence of moderate/severe anemia, symptomatic functional status, and baseline weight <45kg. Predictor of mortality was WHO stage higher than stage I. Male sex, severe anemia, and care in a small clinic were associated with both mortality and LTFU.
Moderate/Advanced HIV disease was predictive of attrition; earlier ART initiation could improve program outcomes. Retention interventions targeting men and those with lower levels of education are needed. Further research to understand geographic and clinic size variations with outcome is warranted.
Data on awareness of HIV status among people living with HIV (PLHIV) are critical to estimating progress toward epidemic control. To ascertain the accuracy of self-reported HIV status and ...antiretroviral drug (ARV) use in the Nigeria HIV/AIDS Indicator and Impact Survey (NAIIS), we compared self-reported HIV status with HIV rapid diagnostic test (RDT) results and self-reported ARV use with detectable blood ARV levels. On the basis of responses and test results, participants were categorized by HIV status and ARV use. Self-reported HIV status and ARV use performance characteristics were determined by estimating sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Proportions and other analyses were weighted to account for complex survey design. During NAIIS, 186,405 participants consented for interview out of which 58,646 reported knowing their HIV status. Of the 959 (weighted, 1.5%) who self-reported being HIV-positive, 849 (92.1%) tested HIV positive and 64 (7.9%) tested HIV negative via RDT and polymerase chain reaction test for discordant positive results. Of the 849 who tested HIV positive, 743 (89.8%) reported using ARV and 72 (10.2%) reported not using ARV. Of 57,687 who self-reported being HIV negative, 686 (1.2%) tested HIV positive via RDT, with ARV biomarkers detected among 195 (25.1%). ARV was detected among 94.5% of those who self-reported using ARV and among 42.0% of those who self-reported not using ARV. Overall, self-reported HIV status had sensitivity of 52.7% (95% confidence interval CI: 49.4%-56.0%) with specificity of 99.9% (95% CI: 99.8%-99.9%). Self-reported ARV use had sensitivity of 95.2% (95% CI: 93.6%-96.7%) and specificity of 54.5% (95% CI: 48.8%-70.7%). Self-reported HIV status and ARV use screening tests were found to be low-validity measures during NAIIS. Laboratory tests to confirm self-reported information may be necessary to determine accurate HIV and clinical status for HIV studies in Nigeria.
BackgroundData on awareness of HIV status among people living with HIV (PLHIV) are critical to estimating progress toward epidemic control. To ascertain the accuracy of self-reported HIV status and ...antiretroviral drug (ARV) use in the Nigeria HIV/AIDS Indicator and Impact Survey (NAIIS), we compared self-reported HIV status with HIV rapid diagnostic test (RDT) results and self-reported ARV use with detectable blood ARV levels.MethodsOn the basis of responses and test results, participants were categorized by HIV status and ARV use. Self-reported HIV status and ARV use performance characteristics were determined by estimating sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Proportions and other analyses were weighted to account for complex survey design.ResultsDuring NAIIS, 186,405 participants consented for interview out of which 58,646 reported knowing their HIV status. Of the 959 (weighted, 1.5%) who self-reported being HIV-positive, 849 (92.1%) tested HIV positive and 64 (7.9%) tested HIV negative via RDT and polymerase chain reaction test for discordant positive results. Of the 849 who tested HIV positive, 743 (89.8%) reported using ARV and 72 (10.2%) reported not using ARV. Of 57,687 who self-reported being HIV negative, 686 (1.2%) tested HIV positive via RDT, with ARV biomarkers detected among 195 (25.1%). ARV was detected among 94.5% of those who self-reported using ARV and among 42.0% of those who self-reported not using ARV. Overall, self-reported HIV status had sensitivity of 52.7% (95% confidence interval CI: 49.4%-56.0%) with specificity of 99.9% (95% CI: 99.8%-99.9%). Self-reported ARV use had sensitivity of 95.2% (95% CI: 93.6%-96.7%) and specificity of 54.5% (95% CI: 48.8%-70.7%).ConclusionsSelf-reported HIV status and ARV use screening tests were found to be low-validity measures during NAIIS. Laboratory tests to confirm self-reported information may be necessary to determine accurate HIV and clinical status for HIV studies in Nigeria.
In Nigeria, results from the pilot of the Test and Treat strategy showed higher loss to follow up (LTFU) among people living with HIV compared to before its implementation. The aim of this evaluation ...was to assess the effects of antiretroviral therapy (ART) initiation within 14 days on LTFU at 12 months and viral suppression. We conducted a retrospective cohort study using routinely collected de-identified patient-level data hosted on the Nigeria National Data Repository from 1,007 facilities. The study population included people living with HIV age greater than or equal to15. We used multivariable Cox proportional frailty hazard models to assess time to LTFU comparing ART initiation strategy and multivariable log-binomial regression for viral suppression. Overall, 26,937 (38.13%) were LTFU at 12 months. Among individuals initiated within 14 days, 38.4% were LTFU by 12 months compared to 35.4% for individuals initiated >14 days (p14 days was not statistically significant. LTFU was higher among individuals who were initiated within 14 days compared to greater than 14 days after HIV diagnosis. There was no difference for viral suppression. The provision of early tailored interventions to support newly diagnosed people living may contribute to reducing LTFU.
Although geographically specific data can help target HIV prevention and treatment strategies, Nigeria relies on national- and state-level estimates for policymaking and intervention planning. We ...calculated sub-state estimates along the HIV continuum of care in Nigeria.
Using data from the Nigeria HIV/AIDS Indicator and Impact Survey (NAIIS) (July-December 2018), we conducted a geospatial analysis estimating three key programmatic indicators: prevalence of HIV infection among adults (aged 15-64 years); antiretroviral therapy (ART) coverage among adults living with HIV; and viral load suppression (VLS) rate among adults living with HIV.
We used an ensemble modeling method called stacked generalization to analyze available covariates and a geostatistical model to incorporate the output from stacking as well as spatial autocorrelation in the modeled outcomes. Separate models were fitted for each indicator. Finally, we produced raster estimates of each indicator on an approximately 5×5-km grid and estimates at the sub-state/local government area (LGA) and state level.
Estimates for all three indicators varied both within and between states. While state-level HIV prevalence ranged from 0.3% (95% uncertainty interval UI: 0.3%-0.5%) to 4.3% (95% UI: 3.7%-4.9%), LGA prevalence ranged from 0.2% (95% UI: 0.1%-0.5%) to 8.5% (95% UI: 5.8%-12.2%). Although the range in ART coverage did not substantially differ at state level (25.6%-76.9%) and LGA level (21.9%-81.9%), the mean absolute difference in ART coverage between LGAs within states was 16.7 percentage points (range, 3.5-38.5 percentage points). States with large differences in ART coverage between LGAs also showed large differences in VLS-regardless of level of effective treatment coverage-indicating that state-level geographic targeting may be insufficient to address coverage gaps.
Geospatial analysis across the HIV continuum of care can effectively highlight sub-state variation and identify areas that require further attention in order to achieve epidemic control. By generating local estimates, governments, donors, and other implementing partners will be better positioned to conduct targeted interventions and prioritize resource distribution.
Background
Ineffective linkage to care (LTC) is a known challenge for community HIV testing. To overcome this challenge, a robust linkage to care strategy was adopted by the 2018 Nigeria HIV/AIDS ...Indicator and Impact Survey (NAIIS). The NAIIS linkage to care strategy was further adapted to improve Nigeria’s programmatic efforts to achieve the 1
st
90 as part of the Nigeria Antiretroviral Therapy (ART) Surge initiative, which also included targeted community testing. In this paper we provide an overview of the NAIIS LTC strategy and describe the impact of this strategy on both the NAIIS and the Surge initiatives.
Methods
The NAIIS collaborated with community-based organizations (CBOs) and deployed mobile health (mHealth) technology with real-time dashboards to manage and optimize community LTC for people living with HIV (PLHIV) diagnosed during the survey. In NAIIS, CBOs’ role was to facilitate linkage of identified PLHIV in community to facility of their choice. For the ART Surge, we modified the NAIIS LTC strategy by empowering both CBOs and mobile community teams as responsible for not only active LTC but also for community testing, ART initiation, and retention in care.
Results
Of the 2,739 PLHIV 15 years and above identified in NAIIS, 1,975 (72.1%) were either unaware of their HIV-positive status (N = 1890) or were aware of their HIV-positive status but not receiving treatment (N = 85). Of these, 1,342 (67.9%) were linked to care, of which 952 (70.9%) were initiated on ART. Among 1,890 newly diagnosed PLHIV, 1,278 (67.6%) were linked to care, 33.7% self-linked and 66.3% were linked by CBOs. Among 85 known PLHIV not on treatment, 64 (75.3%) were linked; 32.8% self-linked and 67.2% were linked by a CBO. In the ART Surge, LTC and treatment initiation rates were 98% and 100%, respectively. Three-month retention for monthly treatment initiation cohorts improved from 76% to 90% over 6 months.
Conclusions
Active LTC strategies by local CBOs and mobile community teams improved LTC and ART initiation in the ART Surge initiative. The use of mHealth technology resulted in timely and accurate documentation of results in NAIIS. By deploying mHealth in addition to active LTC, CBOs and mobile community teams could effectively scale up ART with real-time documentation of client-level outcomes.
Identifying persons who have newly acquired HIV infections is critical for characterizing the HIV epidemic direction. We analyzed pooled data from nationally representative Population-Based HIV ...Impact Assessment surveys conducted across 14 countries in Africa for recent infection risk factors. We included adults 15–49 years of age who had sex during the previous year and used a recent infection testing algorithm to distinguish recent from long-term infections. We collected risk factor information via participant interviews and assessed correlates of recent infection using multinomial logistic regression, incorporating each surveyʼs complex sampling design. Compared with HIV-negative persons, persons with higher odds of recent HIV infection were women, were divorced/separated/widowed, had multiple recent sex partners, had a recent HIV-positive sex partner or one with unknown status, and lived in communities with higher HIV viremia prevalence. Prevention programs focusing on persons at higher risk for HIV and their sexual partners will contribute to reducing HIV incidence.
Abstract
Background
In sub-Saharan Africa, more women than men access HIV testing and treatment and may have better viral load suppression (VLS). We utilized routinely reported aggregated HIV program ...data from 21 sub-Saharan African countries to examine sex differences in VLS and death rates within antiretroviral therapy (ART) programs supported by the United States President's Emergency Plan for AIDS Relief (PEPFAR).
Methods
We included VLS and reported death data for persons aged 15 + years on ART from October–December 2020 disaggregated by sex and age for each subnational unit (SNU). We used linear mixed-model regression to estimate VLS proportion and negative binomial mixed-model regression to estimate the rates of death and death plus interruptions in treatment (IIT). All models were weighted for SNU-level ART population size and adjusted for sex, age, HIV/tuberculosis coinfection, country, and SNU; models for reported deaths and deaths plus IIT were also adjusted for SNU-level VLS.
Results
Mean VLS proportion was higher among women than men (93.0% vs. 92.0%,
p
-value < 0.0001) and 50 + than 15–49 age group (93.7% vs. 91.2%,
p
-value < 0.0001). The mean rate of reported deaths was higher among men than women (2.37 vs. 1.51 per 1000 persons,
p
-value < 0.0001) and 50 + than 15–49 age group (2.39 vs. 1.50 per 1000,
p
-value < 0.0001); the mean rate of reported deaths plus IIT was higher among men (30.1 in men vs. 26.0 in women per 1000,
p
-value < 0.0001) and higher among 15–49 than 50 + age group (34.7 vs. 22.6 per 1000,
p
-value < 0.0001).
Conclusions
The mean rate of reported deaths was higher among men in most models despite adjusting for VLS. Further exploration into differences in care-seeking behaviors; coverage of screening, prophylaxis, and/or treatment of opportunistic infections; and more extensive testing options for men to include CD4 is recommended.
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