Diagnostic performance of Baermann technique, urine-ELISA, stool-PCR and Strongyloides IgG4 rapid test for diagnosis of strongyloidiasis: a study protocol

Résumé fourni par la source

Strongyloidiasis is caused by a parasitic worm, primarily Strongyloides stercoralis . In rural settings of Côte d’Ivoire, parasitological surveys have revealed that the prevalence of S. stercoralis infection can reach up to 50%. The World Health Organization has included S. stercoralis infection among the soil-transmitted helminths that will require particular attention to be effectively controlled by 2030. Although drugs for strongyloidiasis are available, there is a lack of affordable, sensitive and field-applicable diagnostic tools for mapping S. stercoralis infection in low-income endemic areas. The present study aims to determine (i) the diagnostic performance and (ii) the acceptability of Baermann, urine-IgG ELISA, stool-PCR and Strongyloides IgG4 rapid test for S. stercoralis diagnosis. Cross-sectional parasitological surveys will be conducted in 20 villages in the health districts of Agboville and Dabou in the southern part of Côte d’Ivoire. In each village, 60 individuals will be selected at random and invited to provide stool and urine samples. Blood samples will be collected by finger prick. Stool samples will be subjected to duplicate Baermann, duplicate Kato-Katz thick smears and PCR. Urine samples will be examined using filtration, IgG-ELISA and PCR. Strongyloides IgG4 rapid test will be used to analyse blood samples. The prevalence (and whenever possible, the intensity) of S. stercoralis infection will be estimated using the individual diagnostic techniques. Diagnostic performance will be assessed using a composite reference standard. The sensitivity, specificity, positive and negative predictive values of each diagnostic tool for S. stercoralis will be determined. The acceptability of sample collection methods will also be addressed. The study will provide diagnostic performance parameters of different methods for S. stercoralis diagnosis. Our findings will contribute to evidence-based decisions on diagnostic algorithms for large-scale mapping of strongyloidiasis in Côte d’Ivoire and elsewhere.

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