Estimating true prevalence of Schistosoma mansoni from population summary measures based on the Kato-Katz diagnostic technique.

<h4>Background</h4>The prevalence of Schistosoma mansoni infection is usually assessed by the Kato-Katz diagnostic technique. However, Kato-Katz thick smears have low sensitivity, especially for light infections. Egg count models fitted on individual level data can adjust for the infecti...

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Main Authors: Oliver Bärenbold, Amadou Garba, Daniel G Colley, Fiona M Fleming, Rufin K Assaré, Edridah M Tukahebwa, Biruck Kebede, Jean T Coulibaly, Eliézer K N'Goran, Louis-Albert Tchuem Tchuenté, Pauline Mwinzi, Jürg Utzinger, Penelope Vounatsou
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2021-04-01
Series:PLoS Neglected Tropical Diseases
Online Access:https://journals.plos.org/plosntds/article/file?id=10.1371/journal.pntd.0009310&type=printable
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author Oliver Bärenbold
Amadou Garba
Daniel G Colley
Fiona M Fleming
Rufin K Assaré
Edridah M Tukahebwa
Biruck Kebede
Jean T Coulibaly
Eliézer K N'Goran
Louis-Albert Tchuem Tchuenté
Pauline Mwinzi
Jürg Utzinger
Penelope Vounatsou
author_facet Oliver Bärenbold
Amadou Garba
Daniel G Colley
Fiona M Fleming
Rufin K Assaré
Edridah M Tukahebwa
Biruck Kebede
Jean T Coulibaly
Eliézer K N'Goran
Louis-Albert Tchuem Tchuenté
Pauline Mwinzi
Jürg Utzinger
Penelope Vounatsou
author_sort Oliver Bärenbold
collection DOAJ
description <h4>Background</h4>The prevalence of Schistosoma mansoni infection is usually assessed by the Kato-Katz diagnostic technique. However, Kato-Katz thick smears have low sensitivity, especially for light infections. Egg count models fitted on individual level data can adjust for the infection intensity-dependent sensitivity and estimate the 'true' prevalence in a population. However, application of these models is complex and there is a need for adjustments that can be done without modeling expertise. This study provides estimates of the 'true' S. mansoni prevalence from population summary measures of observed prevalence and infection intensity using extensive simulations parametrized with data from different settings in sub-Saharan Africa.<h4>Methodology</h4>An individual-level egg count model was applied to Kato-Katz data to determine the S. mansoni infection intensity-dependent sensitivity for various sampling schemes. Observations in populations with varying forces of transmission were simulated, using standard assumptions about the distribution of worms and their mating behavior. Summary measures such as the geometric mean infection, arithmetic mean infection, and the observed prevalence of the simulations were calculated, and parametric statistical models fitted to the summary measures for each sampling scheme. For validation, the simulation-based estimates are compared with an observational dataset not used to inform the simulation.<h4>Principal findings</h4>Overall, the sensitivity of Kato-Katz in a population varies according to the mean infection intensity. Using a parametric model, which takes into account different sampling schemes varying from single Kato-Katz to triplicate slides over three days, both geometric and arithmetic mean infection intensities improve estimation of sensitivity. The relation between observed and 'true' prevalence is remarkably linear and triplicate slides per day on three consecutive days ensure close to perfect sensitivity.<h4>Conclusions/significance</h4>Estimation of 'true' S. mansoni prevalence is improved when taking into account geometric or arithmetic mean infection intensity in a population. We supply parametric functions and corresponding estimates of their parameters to calculate the 'true' prevalence for sampling schemes up to 3 days with triplicate Kato-Katz thick smears per day that allow estimation of the 'true' prevalence.
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1935-2735
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spelling doaj-art-085c4c4c29e84d0f8bd0bb6411697afe2025-08-20T03:47:07ZengPublic Library of Science (PLoS)PLoS Neglected Tropical Diseases1935-27271935-27352021-04-01154e000931010.1371/journal.pntd.0009310Estimating true prevalence of Schistosoma mansoni from population summary measures based on the Kato-Katz diagnostic technique.Oliver BärenboldAmadou GarbaDaniel G ColleyFiona M FlemingRufin K AssaréEdridah M TukahebwaBiruck KebedeJean T CoulibalyEliézer K N'GoranLouis-Albert Tchuem TchuentéPauline MwinziJürg UtzingerPenelope Vounatsou<h4>Background</h4>The prevalence of Schistosoma mansoni infection is usually assessed by the Kato-Katz diagnostic technique. However, Kato-Katz thick smears have low sensitivity, especially for light infections. Egg count models fitted on individual level data can adjust for the infection intensity-dependent sensitivity and estimate the 'true' prevalence in a population. However, application of these models is complex and there is a need for adjustments that can be done without modeling expertise. This study provides estimates of the 'true' S. mansoni prevalence from population summary measures of observed prevalence and infection intensity using extensive simulations parametrized with data from different settings in sub-Saharan Africa.<h4>Methodology</h4>An individual-level egg count model was applied to Kato-Katz data to determine the S. mansoni infection intensity-dependent sensitivity for various sampling schemes. Observations in populations with varying forces of transmission were simulated, using standard assumptions about the distribution of worms and their mating behavior. Summary measures such as the geometric mean infection, arithmetic mean infection, and the observed prevalence of the simulations were calculated, and parametric statistical models fitted to the summary measures for each sampling scheme. For validation, the simulation-based estimates are compared with an observational dataset not used to inform the simulation.<h4>Principal findings</h4>Overall, the sensitivity of Kato-Katz in a population varies according to the mean infection intensity. Using a parametric model, which takes into account different sampling schemes varying from single Kato-Katz to triplicate slides over three days, both geometric and arithmetic mean infection intensities improve estimation of sensitivity. The relation between observed and 'true' prevalence is remarkably linear and triplicate slides per day on three consecutive days ensure close to perfect sensitivity.<h4>Conclusions/significance</h4>Estimation of 'true' S. mansoni prevalence is improved when taking into account geometric or arithmetic mean infection intensity in a population. We supply parametric functions and corresponding estimates of their parameters to calculate the 'true' prevalence for sampling schemes up to 3 days with triplicate Kato-Katz thick smears per day that allow estimation of the 'true' prevalence.https://journals.plos.org/plosntds/article/file?id=10.1371/journal.pntd.0009310&type=printable
spellingShingle Oliver Bärenbold
Amadou Garba
Daniel G Colley
Fiona M Fleming
Rufin K Assaré
Edridah M Tukahebwa
Biruck Kebede
Jean T Coulibaly
Eliézer K N'Goran
Louis-Albert Tchuem Tchuenté
Pauline Mwinzi
Jürg Utzinger
Penelope Vounatsou
Estimating true prevalence of Schistosoma mansoni from population summary measures based on the Kato-Katz diagnostic technique.
PLoS Neglected Tropical Diseases
title Estimating true prevalence of Schistosoma mansoni from population summary measures based on the Kato-Katz diagnostic technique.
title_full Estimating true prevalence of Schistosoma mansoni from population summary measures based on the Kato-Katz diagnostic technique.
title_fullStr Estimating true prevalence of Schistosoma mansoni from population summary measures based on the Kato-Katz diagnostic technique.
title_full_unstemmed Estimating true prevalence of Schistosoma mansoni from population summary measures based on the Kato-Katz diagnostic technique.
title_short Estimating true prevalence of Schistosoma mansoni from population summary measures based on the Kato-Katz diagnostic technique.
title_sort estimating true prevalence of schistosoma mansoni from population summary measures based on the kato katz diagnostic technique
url https://journals.plos.org/plosntds/article/file?id=10.1371/journal.pntd.0009310&type=printable
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