ArticlePLoS neglected tropical diseases2020
Accuracy of different diagnostic techniques for Schistosoma haematobium to estimate treatment needs in Zimbabwe: Application of a hierarchical Bayesian egg count model.
Article in PLoS neglected tropical diseases, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed, 10 citations in OpenAlex.
- Single-Imaging Parasite-Quantification Microfluidic Device for Detection and Analysis of Schistosoma Eggs in Urine.Micromachines · 2026Article
- Epidemiological situation of schistosomiasis in 16 districts of Burkina Faso after two decades of mass treatment.PLoS neglected tropical diseases · 2025Article
- Re-assessment of schistosomiasis in nine endemic districts with cluster sampling in Sierra Leone.Frontiers in public health · 2024Article
- Review of Recent Prevalence of Urogenital Schistosomiasis in Sub-Saharan Africa and Diagnostic Challenges in the Field Setting.Life (Basel, Switzerland) · 2023Review
- Prevalence and Associated Risk Factors of Urinary Schistosomiasis among Primary School Pupils in the Jidawa and Zobiya Communities of Jigawa State, Nigeria.Annals of global health · 2022Article
- Novel tools and strategies for breaking schistosomiasis transmission: study protocol for an intervention study.BMC infectious diseases · 2021Article
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Authors and funding
8 authors at 3 institutions in 2 countries.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundTreatment needs for Schistosoma haematobium are commonly evaluated using urine filtration with detection of parasite eggs under a microscope. A common symptom of S. haematobium is hematuria, the passing of blood in urine. Hence, the use of hematuria-based diagnostic techniques as a proxy for the assessment of treatment needs has been considered. This study evaluates data from a national survey in Zimbabwe, where three hematuria-based diagnostic techniques, that is microhematuria, macrohematuria, and an anamnestic questionnaire pertaining to self-reported blood in urine, have been included in addition to urine filtration in 280 schools across 70 districts. METHODOLOGY: We developed an egg count model, which evaluates the infection intensity-dependent sensitivity and the specificity of each diagnostic technique without relying on a 'gold' standard. Subsequently, we determined prevalence thresholds for each diagnostic technique, equivalent to a 10% urine filtration-based prevalence and compared classification of districts according to treatment strategy based on the different diagnostic methods. PRINCIPAL
findingsA 10% urine filtration prevalence threshold corresponded to a 17.9% and 13.3% prevalence based on questionnaire and microhematuria, respectively. Both the questionnaire and the microhematuria showed a sensitivity and specificity of more than 85% for estimating treatment needs at the above thresholds. For diagnosis at individual level, the questionnaire showed the highest sensitivity (70.0%) followed by urine filtration (53.8%) and microhematuria (52.2%). CONCLUSIONS/SIGNIFICANCE: The high sensitivity and specificity of a simple questionnaire to estimate treatment needs of S. haematobium suggests that it can be used as a rapid, low-cost method to estimate district prevalence. Our modeling approach can be expanded to include setting-dependent specificity of the technique and should be assessed in relation to other diagnostic methods due to potential cross-reaction with other diseases.
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