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Designing HIV Testing Algorithms Based on 2015 WHO Guidelines Using Data from Six Sites in Sub-Saharan Africa
Cara S Kosack1, Leslie Shanks1, Greet Beelaert2
1Médecins sans Frontières, Amsterdam, Netherlands.
Insights
Evaluating HIV testing algorithms in sub-Saharan Africa showed that while most sites could meet high-prevalence strategy targets, suboptimal rapid diagnostic test (RDT) performance and shared false reactivity limited options. The low-prevalence strategy may be more suitable when tests don't meet specifications.
Area of Science:
- * Medical Diagnostics
- * Public Health
- * Infectious Diseases
Background:
- * Sub-Saharan Africa faces a high burden of Human Immunodeficiency Virus (HIV).
- * Effective HIV testing algorithms are crucial for diagnosis and treatment initiation.
- * World Health Organization (WHO) guidelines recommend specific performance standards for HIV testing algorithms.
Purpose of the Study:
- * To assess the performance of HIV testing algorithms based on WHO recommendations in sub-Saharan Africa.
- * To evaluate the impact of rapid diagnostic test (RDT) performance and shared false reactivity on algorithm effectiveness.
- * To determine the suitability of different HIV testing strategies (high-prevalence vs. low-prevalence) based on site-specific data.
Main Methods:
- * Analysis of 2,780 samples from six HIV testing and counseling sites in sub-Saharan Africa.
- * Design of HIV testing algorithms using Determine as the first test, with second and third RDTs selected based on site performance.
- * Simulation of algorithms adhering to WHO minimum requirements (≥99% sensitivity and specificity), with adjusted thresholds where necessary.
- * Simulation of algorithms with one RDT followed by a simple confirmatory assay.
Main Results:
- * Positive predictive values (PPVs) for simulated algorithms ranged from 75.8% to 100%.
- * Algorithms meeting the recommended ≥99% PPV were achievable in five of six sites using the high-prevalence strategy.
- * Limited options for algorithm design were observed due to suboptimal RDT performance and shared false-reactivity.
Conclusions:
- * The sequence of HIV tests and shared false-reactivity significantly impact algorithm performance.
- * When individual RDTs do not meet WHO-recommended specifications, the low-prevalence strategy may be a more appropriate choice.
- * Site-specific evaluation is essential for optimizing HIV testing algorithm performance in diverse settings.
Abstract:
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.
