Introduction: Rapid diagnostic testing has made HIV diagnosis and subsequent treatment more accessible. However, multiple factors, including improper implementation of testing strategies and clerical errors, have been reported to lead to HIV misdiagnosis. The World Health Organization has recommended HIV retesting prior to antiretroviral therapy (ART) initiation which has become pertinent with scaling up of Early Access to ART for All (EAAA). In this analysis, misdiagnosed clients are identified from a subgroup of clients enrolled in EAAA implementation study in Swaziland. Methods: The subgroup to assess misdiagnosis was identified from enrolled EAAA study clients, who had an undetectable viral load prior to ART initiation between September 1, 2014 and May 31, 2016. One hundred and five of 2533 (4%) clients had an undetectable viral load prior to initiation to ART (pre-ART). The HIV status of clients was confirmed using the Determine HIV 1/2 and Uni-Gold HIV 1/2 rapid tests performed serially as recommended by the national testing algorithm. The status of clients on ART was additionally confirmed by fourth-generation HIV Ag/Ab combo tests, Architect and Genscreen Ultra. Results: Fourteen of the 105 (13%) clients were false positive (HIV negative) on confirmation testing, of whom five (36%) were still in pre-ART care, while nine (64%) were in ART care. Overall, proportion of false positive was 0.6% (14/2533). The false-positive clients had a median CD4 of 791 cells/ml (interquartile range (IQR): 628, 967) compared to 549 cells/ml (IQR: 387, 791) for true positives (HIV positive) (p = 0.0081) and were nearly 20 years older (p = 0.0008). Conclusions: Overall 0.6% of all enrolled EAAA clients were misdiagnosed, and 64% of misdiagnosed clients were initiated on ART. With adoption of EAAA guidelines by national governments, ART initiation regardless of immunological criteria, strengthening of proficiency testing and adoption of retesting prior to ART initiation would allow identification of misdiagnosed clients and further reduce potential of initiating misdiagnosed clients on ART.

BackgroundViral load (VL) testing is being scaled up in resource-limited settings. However, not all commercially available VL testing methods have been evaluated under field conditions. This study is one of a few to evaluate the Biocentric platform for VL quantification in routine practice in Sub-Saharan Africa.MethodsVenous blood specimens were obtained from patients eligible for VL testing at two health facilities in Swaziland from October 2016 to March 2017. Samples were centrifuged at two laboratories (LAB-1, LAB-2) to obtain paired plasma specimens for VL quantification with the national reference method and on the Biocentric platform. Agreement (correlation, Bland–Altman) and accuracy (sensitivity, specificity) indicators were calculated at the VL thresholds of 416 (2.62 log10) and 1000 (3.0 log10) copies/mL. Leftover samples from patients with discordant VL results were re-quantified and accuracy indicators recalculated. Logistic regression was used to compare laboratory performance.ResultsA total of 364 paired plasma samples (LAB-1: n = 198; LAB-2: n = 166) were successfully tested using both methods. The correlation was high (R = 0.82, p < 0.01), and the Bland–Altman analysis showed a minimal mean difference (− 0.03 log10 copies/mL; 95% CI: -1.15 to 1.08). At the clinical threshold level of 3.0 log10 copies/mL, the sensitivity was 88.6% (95% CI: 78.7 to 94.9) and the specificity was 98.3% (95% CI: 96.1 to 99.4). Sensitivity was higher in LAB-1 (100%; 95% CI: 71.5 to 100) than in LAB-2 (86.4%; 95% CI: 75.0 to 94.0). Most upward (n = 8, 2.2%) and downward (n = 11, 3.0%) misclassifications occurred at the 2.62 log threshold, with LAB-2 having a 16 (95% CI: 2.26 to 113.27; p = 0.006) times higher odds of downward misclassification. After retesting of discordant leftover samples (n = 17), overall sensitivity increased to 93.5% (95% CI: 85.5 to 97.9) and 97.1% (95% CI: 90.1 to 99.7) at the 2.62 and 3.0 thresholds, and specificity increased to 98.6% (95% CI: 96.5 to 99.6) and 99.0% (95% CI: 97.0 to 99.8) respectively.ConclusionsThe test characteristics of the Biocentric platform were overall comparable to the national reference method for VL quantification. One laboratory tended to misclassify VL results downwards, likely owing to unmet training needs and lack of previous hands-on practice.Electronic supplementary materialThe online version of this article (10.1186/s12879-018-3474-1) contains supplementary material, which is available to authorized users.

Background:The lack of acute and early HIV infection (AEHI) diagnosis and care contributes to high HIV incidence in resourcelimited settings. We aimed to assess the yield of AEHI, predict and diagnose AEHI, and describe AEHI care outcomes in a public sector setting in Eswatini.Setting: This study was conducted in Nhlangano outpatient department from March 2019 to March 2020.Methods: Adults at risk of AEHI underwent diagnostic testing for AEHI with the quantitative Xpert HIV-1 viral load (VL) assay. AEHI was defined as the detection of HIV-1 VL on Xpert and either an HIV-seronegative or HIV-serodiscordant third-generation antibody-based rapid diagnostic test (RDT) result. First, the crosssectional analysis obtained the yield of AEHI and established a predictor risk score for the prediction of AEHI using Lasso logistic regression. Second, diagnostic accuracy statistics described the ability of the fourth-generation antibody/p24 antigen-based Alere HIV-Combo RDT to diagnose AEHI (vs Xpert VL testing). Third, we described acute HIV infection care outcomes of AEHI-positive patients using survival analysis.Results: Of 795 HIV-seronegative/HIV-serodiscordant outpatients recruited, 30 (3.8%, 95% confidence interval: 2.6% to 5.3%) had AEHI. The predictor risk score contained several factors (HIVserodiscordant RDT, women, feeling at risk of HIV, swollen glands, and fatigue) and had sensitivity and specificity of 83.3% and 65.8%, respectively, to predict AEHI. The HIV-Combo RDT had sensitivity and specificity of 86.2% and 99.9%, respectively, to diagnose AEHI. Of 30 AEHI-positive patients, the 1-month cumulative treatment initiation was 74% (95% confidence interval: 57% to 88%), and the 3-month viral suppression (,1000 copies/mL) was 87% (67% to 98%).Conclusion: AEHI diagnosis and care seem possible in resourcelimited settings.

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