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 300 million clinical cases are declared every year. The level of infection, expressed as parasite densit...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Imen Hammami, Grégory Nuel, André Garcia
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2013
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/8cb2774d89974922afecdb17d188eeeb
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:8cb2774d89974922afecdb17d188eeeb
record_format	dspace
spelling	oai:doaj.org-article:8cb2774d89974922afecdb17d188eeeb2021-11-18T07:53:31ZStatistical properties of parasite density estimators in malaria.1932-620310.1371/journal.pone.0051987https://doaj.org/article/8cb2774d89974922afecdb17d188eeeb2013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23516389/?tool=EBIhttps://doaj.org/toc/1932-6203Malaria 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 300 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.Imen HammamiGrégory NuelAndré GarciaPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 8, Iss 3, p e51987 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Imen Hammami Grégory Nuel André Garcia Statistical properties of parasite density estimators in malaria.
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 300 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.
format	article
author	Imen Hammami Grégory Nuel André Garcia
author_facet	Imen Hammami Grégory Nuel André Garcia
author_sort	Imen Hammami
title	Statistical properties of parasite density estimators in malaria.
title_short	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_sort	statistical properties of parasite density estimators in malaria.
publisher	Public Library of Science (PLoS)
publishDate	2013
url	https://doaj.org/article/8cb2774d89974922afecdb17d188eeeb
work_keys_str_mv	AT imenhammami statisticalpropertiesofparasitedensityestimatorsinmalaria AT gregorynuel statisticalpropertiesofparasitedensityestimatorsinmalaria AT andregarcia statisticalpropertiesofparasitedensityestimatorsinmalaria
_version_	1718422817923399680

Statistical properties of parasite density estimators in malaria.

Ejemplares similares