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Statistical Properties of Parasite Density Estimators in Malaria

Malaria is a global health problem responsible for nearly one million deaths every year around 85% of which concern children younger than five years old in Sub-Saharan Africa. In addition, around [Image: see text] million clinical cases are declared every year. The level of infection, expressed as p...

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Detalles Bibliográficos
Autores principales: Hammami, Imen, Nuel, Grégory, Garcia, André
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3597708/
https://www.ncbi.nlm.nih.gov/pubmed/23516389
http://dx.doi.org/10.1371/journal.pone.0051987
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author Hammami, Imen
Nuel, Grégory
Garcia, André
author_facet Hammami, Imen
Nuel, Grégory
Garcia, André
author_sort Hammami, Imen
collection PubMed
description Malaria is a global health problem responsible for nearly one million deaths every year around 85% of which concern children younger than five years old in Sub-Saharan Africa. In addition, around [Image: see text] million clinical cases are declared every year. The level of infection, expressed as parasite density, is classically defined as the number of asexual parasites relative to a microliter of blood. Microscopy of Giemsa-stained thick blood films is the gold standard for parasite enumeration. Parasite density estimation methods usually involve threshold values; either the number of white blood cells counted or the number of high power fields read. However, the statistical properties of parasite density estimators generated by these methods have largely been overlooked. Here, we studied the statistical properties (mean error, coefficient of variation, false negative rates) of parasite density estimators of commonly used threshold-based counting techniques depending on variable threshold values. We also assessed the influence of the thresholds on the cost-effectiveness of parasite density estimation methods. In addition, we gave more insights on the behavior of measurement errors according to varying threshold values, and on what should be the optimal threshold values that minimize this variability.
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spelling pubmed-35977082013-03-20 Statistical Properties of Parasite Density Estimators in Malaria Hammami, Imen Nuel, Grégory Garcia, André PLoS One Research Article Malaria is a global health problem responsible for nearly one million deaths every year around 85% of which concern children younger than five years old in Sub-Saharan Africa. In addition, around [Image: see text] million clinical cases are declared every year. The level of infection, expressed as parasite density, is classically defined as the number of asexual parasites relative to a microliter of blood. Microscopy of Giemsa-stained thick blood films is the gold standard for parasite enumeration. Parasite density estimation methods usually involve threshold values; either the number of white blood cells counted or the number of high power fields read. However, the statistical properties of parasite density estimators generated by these methods have largely been overlooked. Here, we studied the statistical properties (mean error, coefficient of variation, false negative rates) of parasite density estimators of commonly used threshold-based counting techniques depending on variable threshold values. We also assessed the influence of the thresholds on the cost-effectiveness of parasite density estimation methods. In addition, we gave more insights on the behavior of measurement errors according to varying threshold values, and on what should be the optimal threshold values that minimize this variability. Public Library of Science 2013-03-14 /pmc/articles/PMC3597708/ /pubmed/23516389 http://dx.doi.org/10.1371/journal.pone.0051987 Text en © 2013 Hammami 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, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Hammami, Imen
Nuel, Grégory
Garcia, André
Statistical Properties of Parasite Density Estimators in Malaria
title Statistical Properties of Parasite Density Estimators in Malaria
title_full Statistical Properties of Parasite Density Estimators in Malaria
title_fullStr Statistical Properties of Parasite Density Estimators in Malaria
title_full_unstemmed Statistical Properties of Parasite Density Estimators in Malaria
title_short Statistical Properties of Parasite Density Estimators in Malaria
title_sort statistical properties of parasite density estimators in malaria
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3597708/
https://www.ncbi.nlm.nih.gov/pubmed/23516389
http://dx.doi.org/10.1371/journal.pone.0051987
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