Abstract
BackgroundAlgorithms to diagnose gambiense human African trypanosomiasis (HAT, sleeping sickness) are often complex due to the unsatisfactory sensitivity and/or specificity of available tests, and typically include a screening (serological), confirmation (parasitological) and staging component. There is insufficient evidence on the relative accuracy of these algorithms. This paper presents estimates of the accuracy of five algorithms used by past Médecins Sans Frontières programmes in the Republic of Congo, Southern Sudan and Uganda.Methodology and Principal FindingsThe sequence of tests in each algorithm was programmed into a probabilistic model, informed by distributions of the sensitivity, specificity and staging accuracy of each test, constructed based on a literature review. The accuracy of algorithms was estimated in a baseline scenario and in a worst-case scenario introducing various near worst-case assumptions. In the baseline scenario, sensitivity was estimated as 85–90% in all but one algorithm, with specificity above 99.9% except for the Republic of Congo, where CATT serology was used as independent confirmation test: here, positive predictive value (PPV) was estimated at <50% in realistic active screening prevalence scenarios. Furthermore, most algorithms misclassified about one third of true stage 1 cases as stage 2, and about 10% of true stage 2 cases as stage 1. In the worst-case scenario, sensitivity was 75–90% and PPV no more than 75% at 1% prevalence, with about half of stage 1 cases misclassified as stage 2.ConclusionsPublished evidence on the accuracy of widely used tests is scanty. Algorithms should carefully weigh the use of serology alone for confirmation, and could enhance sensitivity through serological suspect follow-up and repeat parasitology. Better evidence on the frequency of low-parasitaemia infections is needed. Simulation studies should guide the tailoring of algorithms to specific scenarios of HAT prevalence and availability of control tools.
Highlights
The diagnosis of gambiense human African trypanosomiasis (HAT, sleeping sickness) in routine conditions is complex [1]
Parasitological positives (T+) undergo lumbar puncture and are classified as stage 2 if parasites are found in cerebrospinal fluid (CSF), or if a given threshold of CSF white blood cell (WBC) density is exceeded [5]
Interpretation of findings This study suggests that diagnostic algorithms previously used by Medecins Sans Frontieres (MSF) had a sensitivity of 85–90% in a baseline scenario analysis, except for an algorithm in Southern Sudan in which only individuals Card Agglutination Test for Trypanosomiasis (CATT)$1:16 positive underwent blood and CSF
Summary
The diagnosis of gambiense human African trypanosomiasis (HAT, sleeping sickness) in routine conditions is complex [1]. Diagnostic algorithms combine several tests and feature a screening, confirmation and staging component. The Card Agglutination Test for Trypanosomiasis (CATT) [4], highly sensitive when performed in whole blood (CATT-wb) but insufficiently specific (,96%), is used for screening. After CATT-wb or CATT plasma screening, various parasitological confirmation tests are applied either alone or in sequence on blood and/or neck gland aspirate, so as to maximise specificity while maintaining acceptable levels of sensitivity. Individuals with strong CATT reactions (dilutions $1:4) but no parasitological evidence of infection (T2) are generally considered serological suspects. Algorithms to diagnose gambiense human African trypanosomiasis (HAT, sleeping sickness) are often complex due to the unsatisfactory sensitivity and/or specificity of available tests, and typically include a screening (serological), confirmation (parasitological) and staging component. This paper presents estimates of the accuracy of five algorithms used by past Medecins Sans Frontieres programmes in the Republic of Congo, Southern Sudan and Uganda
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