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Accuracy of different diagnostic techniques for Schistosoma haematobium to estimate treatment needs in Zimbabwe: Application of a hierarchical Bayesian egg count model

BACKGROUND: Treatment 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...

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Autores principales: Midzi, Nicholas, Bärenbold, Oliver, Manangazira, Portia, Phiri, Isaac, Mutsaka-Makuvaza, Masceline J., Mhlanga, Gibson, Utzinger, Jürg, Vounatsou, Penelope
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7462259/
https://www.ncbi.nlm.nih.gov/pubmed/32817650
http://dx.doi.org/10.1371/journal.pntd.0008451
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author Midzi, Nicholas
Bärenbold, Oliver
Manangazira, Portia
Phiri, Isaac
Mutsaka-Makuvaza, Masceline J.
Mhlanga, Gibson
Utzinger, Jürg
Vounatsou, Penelope
author_facet Midzi, Nicholas
Bärenbold, Oliver
Manangazira, Portia
Phiri, Isaac
Mutsaka-Makuvaza, Masceline J.
Mhlanga, Gibson
Utzinger, Jürg
Vounatsou, Penelope
author_sort Midzi, Nicholas
collection PubMed
description BACKGROUND: Treatment 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 FINDINGS: A 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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spelling pubmed-74622592020-09-04 Accuracy of different diagnostic techniques for Schistosoma haematobium to estimate treatment needs in Zimbabwe: Application of a hierarchical Bayesian egg count model Midzi, Nicholas Bärenbold, Oliver Manangazira, Portia Phiri, Isaac Mutsaka-Makuvaza, Masceline J. Mhlanga, Gibson Utzinger, Jürg Vounatsou, Penelope PLoS Negl Trop Dis Research Article BACKGROUND: Treatment 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 FINDINGS: A 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. Public Library of Science 2020-08-20 /pmc/articles/PMC7462259/ /pubmed/32817650 http://dx.doi.org/10.1371/journal.pntd.0008451 Text en © 2020 Midzi et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Midzi, Nicholas
Bärenbold, Oliver
Manangazira, Portia
Phiri, Isaac
Mutsaka-Makuvaza, Masceline J.
Mhlanga, Gibson
Utzinger, Jürg
Vounatsou, Penelope
Accuracy of different diagnostic techniques for Schistosoma haematobium to estimate treatment needs in Zimbabwe: Application of a hierarchical Bayesian egg count model
title Accuracy of different diagnostic techniques for Schistosoma haematobium to estimate treatment needs in Zimbabwe: Application of a hierarchical Bayesian egg count model
title_full Accuracy of different diagnostic techniques for Schistosoma haematobium to estimate treatment needs in Zimbabwe: Application of a hierarchical Bayesian egg count model
title_fullStr Accuracy of different diagnostic techniques for Schistosoma haematobium to estimate treatment needs in Zimbabwe: Application of a hierarchical Bayesian egg count model
title_full_unstemmed Accuracy of different diagnostic techniques for Schistosoma haematobium to estimate treatment needs in Zimbabwe: Application of a hierarchical Bayesian egg count model
title_short Accuracy of different diagnostic techniques for Schistosoma haematobium to estimate treatment needs in Zimbabwe: Application of a hierarchical Bayesian egg count model
title_sort accuracy of different diagnostic techniques for schistosoma haematobium to estimate treatment needs in zimbabwe: application of a hierarchical bayesian egg count model
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7462259/
https://www.ncbi.nlm.nih.gov/pubmed/32817650
http://dx.doi.org/10.1371/journal.pntd.0008451
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