True malaria prevalence in children under five: Bayesian estimation using data of malaria household surveys from three sub-Saharan countries.

<h4>Background</h4> <p>Malaria is one of the major causes of childhood death in sub-Saharan countries. A reliable estimation of malaria prevalence is important to guide and monitor progress toward control and elimination. The aim of the study was to estimate the true prevalence of...

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Main Authors: Mfueni, E, Devleesschauwer, B, Rosas-Aguirre, A, Van Malderen, C, Brandt, P, Ogutu, B, Snow, R, Tshilolo, L, Zurovac, D, Vanderelst, D, Speybroeck, N
Format: Journal article
Language:English
Published: BioMed Central 2018
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author Mfueni, E
Devleesschauwer, B
Rosas-Aguirre, A
Van Malderen, C
Brandt, P
Ogutu, B
Snow, R
Tshilolo, L
Zurovac, D
Vanderelst, D
Speybroeck, N
author_facet Mfueni, E
Devleesschauwer, B
Rosas-Aguirre, A
Van Malderen, C
Brandt, P
Ogutu, B
Snow, R
Tshilolo, L
Zurovac, D
Vanderelst, D
Speybroeck, N
author_sort Mfueni, E
collection OXFORD
description <h4>Background</h4> <p>Malaria is one of the major causes of childhood death in sub-Saharan countries. A reliable estimation of malaria prevalence is important to guide and monitor progress toward control and elimination. The aim of the study was to estimate the true prevalence of malaria in children under five in the Democratic Republic of the Congo, Uganda and Kenya, using a Bayesian modelling framework that combined in a novel way malaria data from national household surveys with external information about the sensitivity and specificity of the malaria diagnostic methods used in those surveys—i.e., rapid diagnostic tests and light microscopy.</p> <h4>Methods</h4> <p>Data were used from the Demographic and Health Surveys (DHS) and Malaria Indicator Surveys (MIS) conducted in the Democratic Republic of the Congo (DHS 2013–2014), Uganda (MIS 2014–2015) and Kenya (MIS 2015), where information on infection status using rapid diagnostic tests and/or light microscopy was available for 13,573 children. True prevalence was estimated using a Bayesian model that accounted for the conditional dependence between the two diagnostic methods, and the uncertainty of their sensitivities and specificities obtained from expert opinion.</p> <h4>Results</h4> <p>The estimated true malaria prevalence was 20% (95% uncertainty interval [UI] 17%–23%) in the Democratic Republic of the Congo, 22% (95% UI 9–32%) in Uganda and 1% (95% UI 0–3%) in Kenya. According to the model estimations, rapid diagnostic tests had a satisfactory sensitivity and specificity, and light microscopy had a variable sensitivity, but a satisfactory specificity. Adding reported history of fever in the previous 14 days as a third diagnostic method to the model did not affect model estimates, highlighting the poor performance of this indicator as a malaria diagnostic.</p> <h4>Conclusions</h4> <p>In the absence of a gold standard test, Bayesian models can assist in the optimal estimation of the malaria burden, using individual results from several tests and expert opinion about the performance of those tests.</p>
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spelling oxford-uuid:278f20b1-332e-4d1e-8ce5-1e10f14f3f912022-03-26T12:07:48ZTrue malaria prevalence in children under five: Bayesian estimation using data of malaria household surveys from three sub-Saharan countries.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:278f20b1-332e-4d1e-8ce5-1e10f14f3f91EnglishSymplectic Elements at OxfordBioMed Central2018Mfueni, EDevleesschauwer, BRosas-Aguirre, AVan Malderen, CBrandt, POgutu, BSnow, RTshilolo, LZurovac, DVanderelst, DSpeybroeck, N <h4>Background</h4> <p>Malaria is one of the major causes of childhood death in sub-Saharan countries. A reliable estimation of malaria prevalence is important to guide and monitor progress toward control and elimination. The aim of the study was to estimate the true prevalence of malaria in children under five in the Democratic Republic of the Congo, Uganda and Kenya, using a Bayesian modelling framework that combined in a novel way malaria data from national household surveys with external information about the sensitivity and specificity of the malaria diagnostic methods used in those surveys—i.e., rapid diagnostic tests and light microscopy.</p> <h4>Methods</h4> <p>Data were used from the Demographic and Health Surveys (DHS) and Malaria Indicator Surveys (MIS) conducted in the Democratic Republic of the Congo (DHS 2013–2014), Uganda (MIS 2014–2015) and Kenya (MIS 2015), where information on infection status using rapid diagnostic tests and/or light microscopy was available for 13,573 children. True prevalence was estimated using a Bayesian model that accounted for the conditional dependence between the two diagnostic methods, and the uncertainty of their sensitivities and specificities obtained from expert opinion.</p> <h4>Results</h4> <p>The estimated true malaria prevalence was 20% (95% uncertainty interval [UI] 17%–23%) in the Democratic Republic of the Congo, 22% (95% UI 9–32%) in Uganda and 1% (95% UI 0–3%) in Kenya. According to the model estimations, rapid diagnostic tests had a satisfactory sensitivity and specificity, and light microscopy had a variable sensitivity, but a satisfactory specificity. Adding reported history of fever in the previous 14 days as a third diagnostic method to the model did not affect model estimates, highlighting the poor performance of this indicator as a malaria diagnostic.</p> <h4>Conclusions</h4> <p>In the absence of a gold standard test, Bayesian models can assist in the optimal estimation of the malaria burden, using individual results from several tests and expert opinion about the performance of those tests.</p>
spellingShingle Mfueni, E
Devleesschauwer, B
Rosas-Aguirre, A
Van Malderen, C
Brandt, P
Ogutu, B
Snow, R
Tshilolo, L
Zurovac, D
Vanderelst, D
Speybroeck, N
True malaria prevalence in children under five: Bayesian estimation using data of malaria household surveys from three sub-Saharan countries.
title True malaria prevalence in children under five: Bayesian estimation using data of malaria household surveys from three sub-Saharan countries.
title_full True malaria prevalence in children under five: Bayesian estimation using data of malaria household surveys from three sub-Saharan countries.
title_fullStr True malaria prevalence in children under five: Bayesian estimation using data of malaria household surveys from three sub-Saharan countries.
title_full_unstemmed True malaria prevalence in children under five: Bayesian estimation using data of malaria household surveys from three sub-Saharan countries.
title_short True malaria prevalence in children under five: Bayesian estimation using data of malaria household surveys from three sub-Saharan countries.
title_sort true malaria prevalence in children under five bayesian estimation using data of malaria household surveys from three sub saharan countries
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