Performance of a real-time PCR approach for diagnosing Schistosoma haematobium infections of different intensity in urine samples from Zanzibar

Autor: Dominique Keller, Julian Rothen, Jean-Pierre Dangy, Corina Saner, Claudia Daubenberger, Fiona Allan, Shaali M. Ame, Said M. Ali, Fatma Kabole, Jan Hattendorf, David Rollinson, Ralf Seyfarth, Stefanie Knopp
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Infectious Diseases of Poverty, Vol 9, Iss 1, Pp 1-13 (2020)
Druh dokumentu: article
ISSN: 2049-9957
DOI: 10.1186/s40249-020-00726-y
Popis: Abstract Background Efforts to control and eliminate schistosomiasis have accelerated over the past decade. As parasite burden, associated morbidity and egg excretion decrease, diagnosis with standard parasitological methods becomes harder. We assessed the robustness and performance of a real-time PCR (qPCR) approach in comparison with urine filtration microscopy and reagent strip testing for the diagnosis of Schistosoma haematobium infections of different intensities. Methods The robustness of DNA isolation and qPCR was validated in eight laboratories from Europe and Africa. Subsequently, 792 urine samples collected during cross-sectional surveys of the Zanzibar Elimination of Schistosomiasis Transmission (ZEST) project in 2012–2017 were examined with qPCR in 2018. Diagnostic sensitivity of the qPCR was calculated at different infection intensity categories, using urine filtration microscopy as reference test. Spearman’s rank correlation between Ct-values and S. haematobium egg counts was assessed and Ct-value percentiles for infection intensity categories determined. Results S. haematobium Dra1 DNA-positive samples were identified correctly in all eight laboratories. Examination of urine samples from Zanzibar revealed Dra1 DNA in 26.8% (212/792) by qPCR, S. haematobium eggs in 13.3% (105/792) by urine filtration, and microhaematuria in 13.8% (109/792) by reagent strips. Sensitivity of the qPCR increased with augmenting egg counts: 80.6% (29/36) for counts between 1 and 4 eggs, 83.3% (15/18) for counts between 5 and 9 eggs, 100% (23/23) for counts between 10 and 49 eggs, and 96.4% (27/28) for counts of 50+ eggs. There was a significant negative correlation between Ct-values and egg counts (Spearman’s rho = − 0.49, P
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