Laboratory and clinical diagnostic classification of seropositive individuals, followed by treatment and supportive therapy, is an established component of Chagas' disease control in areas where this disease is endemic. However, most Chagas' disease patients live in remote areas where neither equipped laboratories nor skilled human resources are widely available. Employing a rapid diagnostic test (RDT), when using whole blood samples, is the best option for Chagas' disease control. A high sensitivity and specificity for the Chagas Stat-Pak RDT (Chembio Diagnostic Systems, Inc., Medford, NY) has been reported for assays using serum and plasma, but its validity for the detection of antibodies to Trypanosoma cruzi infection in whole blood is unknown. This cross-sectional study measured the sensitivity and specificity of the Chagas Stat-Pak with whole blood, using conventional serological assays for comparison.

IntroductionAs antiretroviral therapy (ART) is scaled up, more patients become eligible for routine viral load (VL) monitoring, the most important tool for monitoring ART efficacy. For HIV programmes to become effective, leakages along the VL cascade need to be minimized and treatment switching needs to be optimized. However, many HIV programmes in resource‐constrained settings report significant shortfalls.MethodsFrom a public sector HIV programme in rural Swaziland, we evaluated the VL cascade of adults (≥18 years) on ART from the time of the first elevated VL (>1000 copies/mL) between January 2013 and June 2014 to treatment switching by December 2015. We additionally described HIV drug resistance for patients with virological failure. We used descriptive statistics and Kaplan–Meier estimates to describe the different steps along the cascade and regression models to determine factors associated with outcomes.Results and DiscussionOf 828 patients with a first elevated VL, 252 (30.4%) did not receive any enhanced adherence counselling (EAC). Six hundred and ninety‐six (84.1%) patients had a follow‐up VL measurement, and the predictors of receiving a follow‐up VL were being a second‐line patient (adjusted hazard ratio (aHR): 0.72; p = 0.051), Hlathikhulu health zone (aHR: 0.79; p = 0.013) and having received two EAC sessions (aHR: 1.31; p = 0.023). Four hundred and ten patients (58.9%) achieved VL re‐suppression. Predictors of re‐suppression were age 50 to 64 (adjusted odds ratio (aOR): 2.02; p = 0.015) compared with age 18 to 34 years, being on second‐line treatment (aOR: 3.29; p = 0.003) and two (aOR: 1.66; p = 0.045) or three (aOR: 1.86; p = 0.003) EAC sessions. Of 278 patients eligible to switch to second‐line therapy, 120 (43.2%) had switched by the end of the study. Finally, of 155 successfully sequenced dried blood spots, 144 (92.9%) were from first‐line patients. Of these, 133 (positive predictive value: 92.4%) had resistance patterns that necessitated treatment switching.ConclusionsPatients on ART with high VLs were more likely to re‐suppress if they received EAC. Failure to re‐suppress after counselling was predictive of genotypically confirmed resistance patterns requiring treatment switching. Delays in switching were significant despite the ability of the WHO algorithm to predict treatment failure. Despite significant progress in recent years, enhanced focus on quality care along the VL cascade in resource‐limited settings is crucial.

Trypanosoma cruzi infection is often not detected early on or actively diagnosed, partly because most infected individuals are either asymptomatic or oligosymptomatic. Moreover, in most places, neither blood banks nor healthcare units offer diagnostic confirmation or treatment access. By the time patients present clinical manifestations of advanced chronic Chagas disease, specific treatment with current drugs usually has limited effectiveness. Better-quality serological assays are urgently needed, especially rapid diagnostic tests for diagnosis patients in both acute and chronic phases, as well as for confirming that a parasitological cure has been achieved. Some new antigen combinations look promising and it is important to assess which ones are potentially the best, together with their requirements in terms of investigation and development. In August 2007, a group of specialized researchers and healthcare professionals met to discuss the state of Chagas infection diagnosis and to build a consensus for a plan of action to develop efficient, affordable, accessible and easy-to-use diagnostic tests for Chagas disease. This technical report presents the conclusions from that meeting.

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.

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