Designing HIV Testing Algorithms Based on 2015 WHO Guidelines Using Data from Six Sites in Sub-Saharan Africa.

Our objective was to evaluate the performance of HIV testing algorithms based on WHO recommendations, using data from specimens collected at six HIV testing and counseling sites in sub-Saharan Africa (Conakry, Guinea; Kitgum and Arua, Uganda; Homa Bay, Kenya; Douala, Cameroon; Baraka, Democratic Republic of Congo). A total of 2,780 samples, including 1,306 HIV-positive samples, were included in the analysis. HIV testing algorithms were designed using Determine as a first test. Second and third rapid diagnostic tests (RDTs) were selected based on site-specific performance, adhering where possible to the WHO-recommended minimum requirements of ≥99% sensitivity and specificity. The threshold for specificity was reduced to 98% or 96% if necessary. We also simulated algorithms consisting of one RDT followed by a simple confirmatory assay. The positive predictive values (PPV) of the simulated algorithms ranged from 75.8% to 100% using strategies recommended for high-prevalence settings, 98.7% to 100% using strategies recommended for low-prevalence settings, and 98.1% to 100% using a rapid test followed by a simple confirmatory assay. Although we were able to design algorithms that met the recommended PPV of ≥99% in five of six sites using the applicable high-prevalence strategy, options were often very limited due to suboptimal performance of individual RDTs and to shared falsely reactive results. These results underscore the impact of the sequence of HIV tests and of shared false-reactivity data on algorithm performance. Where it is not possible to identify tests that meet WHO-recommended specifications, the low-prevalence strategy may be more suitable.

HIV misdiagnosis in sub-Saharan Africa: performance of diagnostic algorithms at six testing sites.

INTRODUCTION: We evaluated the diagnostic accuracy of HIV testing algorithms at six programmes in five sub-Saharan African countries. METHODS: In this prospective multisite diagnostic evaluation study (Conakry, Guinea; Kitgum, Uganda; Arua, Uganda; Homa Bay, Kenya; Doula, Cameroun and Baraka, Democratic Republic of Congo), samples from clients (greater than equal to five years of age) testing for HIV were collected and compared to a state-of-the-art algorithm from the AIDS reference laboratory at the Institute of Tropical Medicine, Belgium. The reference algorithm consisted of an enzyme-linked immuno-sorbent assay, a line-immunoassay, a single antigen-enzyme immunoassay and a DNA polymerase chain reaction test. RESULTS: Between August 2011 and January 2015, over 14,000 clients were tested for HIV at 6 HIV counselling and testing sites. Of those, 2786 (median age: 30; 38.1% males) were included in the study. Sensitivity of the testing algorithms ranged from 89.5% in Arua to 100% in Douala and Conakry, while specificity ranged from 98.3% in Doula to 100% in Conakry. Overall, 24 (0.9%) clients, and as many as 8 per site (1.7%), were misdiagnosed, with 16 false-positive and 8 false-negative results. Six false-negative specimens were retested with the on-site algorithm on the same sample and were found to be positive. Conversely, 13 false-positive specimens were retested: 8 remained false-positive with the on-site algorithm. CONCLUSIONS: The performance of algorithms at several sites failed to meet expectations and thresholds set by the World Health Organization, with unacceptably high rates of false results. Alongside the careful selection of rapid diagnostic tests and the validation of algorithms, strictly observing correct procedures can reduce the risk of false results. In the meantime, to identify false-positive diagnoses at initial testing, patients should be retested upon initiating antiretroviral therapy.

Towards more accurate HIV testing in sub-Saharan Africa: a multi-site evaluation of HIV RDTs and risk factors for false positives.

INTRODUCTION: Although individual HIV rapid diagnostic tests (RDTs) show good performance in evaluations conducted by WHO, reports from several African countries highlight potentially significant performance issues. Despite widespread use of RDTs for HIV diagnosis in resource-constrained settings, there has been no systematic, head-to-head evaluation of their accuracy with specimens from diverse settings across sub-Saharan Africa. We conducted a standardized, centralized evaluation of eight HIV RDTs and two simple confirmatory assays at a WHO collaborating centre for evaluation of HIV diagnostics using specimens from six sites in five sub-Saharan African countries. METHODS: Specimens were transported to the Institute of Tropical Medicine (ITM), Antwerp, Belgium for testing. The tests were evaluated by comparing their results to a state-of-the-art reference algorithm to estimate sensitivity, specificity and predictive values. RESULTS: 2785 samples collected from August 2011 to January 2015 were tested at ITM. All RDTs showed very high sensitivity, from 98.8% for First Response HIV Card Test 1-2.0 to 100% for Determine HIV 1/2, Genie Fast, SD Bioline HIV 1/2 3.0 and INSTI HIV-1/HIV-2 Antibody Test kit. Specificity ranged from 90.4% for First Response to 99.7% for HIV 1/2 STAT-PAK with wide variation based on the geographical origin of specimens. Multivariate analysis showed several factors were associated with false-positive results, including gender, provider-initiated testing and the geographical origin of specimens. For simple confirmatory assays, the total sensitivity and specificity was 100% and 98.8% for ImmunoComb II HIV 12 CombFirm (ImmunoComb) and 99.7% and 98.4% for Geenius HIV 1/2 with indeterminate rates of 8.9% and 9.4%. CONCLUSION: In this first systematic head-to-head evaluation of the most widely used RDTs, individual RDTs performed more poorly than in the WHO evaluations: only one test met the recommended thresholds for RDTs of ≥99% sensitivity and ≥98% specificity. By performing all tests in a centralized setting, we show that these differences in performance cannot be attributed to study procedure, end-user variation, storage conditions, or other methodological factors. These results highlight the existence of geographical and population differences in individual HIV RDT performance and underscore the challenges of designing locally validated algorithms that meet the latest WHO-recommended thresholds.