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Combining different diagnostic studies of lymphatic filariasis for risk mapping in Papua New Guinea: a predictive model from microfilaraemia and antigenaemia prevalence surveys

BACKGROUND: The Global Programme to Eliminate Lymphatic Filariasis has encouraged countries to follow a set of guidelines to help them assess the need for mass drug administration and evaluate its progress. Papua New Guinea (PNG) is one of the highest priority countries in the Western Pacific for ly...

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Autores principales: Berg Soto, Alvaro, Xu, Zhijing, Wood, Peter, Sanuku, Nelly, Robinson, Leanne J., King, Christopher L., Tisch, Daniel, Susapu, Melinda, Graves, Patricia M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6280391/
https://www.ncbi.nlm.nih.gov/pubmed/30533996
http://dx.doi.org/10.1186/s41182-018-0123-8
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author Berg Soto, Alvaro
Xu, Zhijing
Wood, Peter
Sanuku, Nelly
Robinson, Leanne J.
King, Christopher L.
Tisch, Daniel
Susapu, Melinda
Graves, Patricia M.
author_facet Berg Soto, Alvaro
Xu, Zhijing
Wood, Peter
Sanuku, Nelly
Robinson, Leanne J.
King, Christopher L.
Tisch, Daniel
Susapu, Melinda
Graves, Patricia M.
author_sort Berg Soto, Alvaro
collection PubMed
description BACKGROUND: The Global Programme to Eliminate Lymphatic Filariasis has encouraged countries to follow a set of guidelines to help them assess the need for mass drug administration and evaluate its progress. Papua New Guinea (PNG) is one of the highest priority countries in the Western Pacific for lymphatic filariasis and the site of extensive research on lymphatic filariasis and surveys of its prevalence. However, different diagnostic tests have been used and thresholds for each test are unclear. METHODS: We reviewed the prevalence of lymphatic filariasis reported in 295 surveys conducted in PNG between 1990 and 2014, of which 65 used more than one test. Results from different diagnostics were standardised using a set of criteria that included a model to predict antigen prevalence from microfilariae prevalence. We mapped the point location of each of these surveys and categorised their standardised prevalence estimates. RESULTS: Several predictive models were produced and investigated, including the effect of any mass drug administration and number of rounds prior to the surveys. One model was chosen based on goodness of fit parameters and used to predict antigen prevalence for surveys that tested only for microfilariae. Standardised prevalence values show that 72% of all surveys reported a prevalence above 0.05. High prevalence was situated on the coastal north, south and island regions, while the central highland area of Papua New Guinea shows low levels of prevalence. CONCLUSIONS: Our study is the first to provide an explicit predictive relationship between the prevalence values based on empirical results from antigen and microfilaria tests, taking into account the occurrence of mass drug administration. This is a crucial step to combine studies to develop risk maps of lymphatic filariasis for programme planning and evaluation, as shown in the case of Papua New Guinea. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s41182-018-0123-8) contains supplementary material, which is available to authorized users.
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spelling pubmed-62803912018-12-10 Combining different diagnostic studies of lymphatic filariasis for risk mapping in Papua New Guinea: a predictive model from microfilaraemia and antigenaemia prevalence surveys Berg Soto, Alvaro Xu, Zhijing Wood, Peter Sanuku, Nelly Robinson, Leanne J. King, Christopher L. Tisch, Daniel Susapu, Melinda Graves, Patricia M. Trop Med Health Research BACKGROUND: The Global Programme to Eliminate Lymphatic Filariasis has encouraged countries to follow a set of guidelines to help them assess the need for mass drug administration and evaluate its progress. Papua New Guinea (PNG) is one of the highest priority countries in the Western Pacific for lymphatic filariasis and the site of extensive research on lymphatic filariasis and surveys of its prevalence. However, different diagnostic tests have been used and thresholds for each test are unclear. METHODS: We reviewed the prevalence of lymphatic filariasis reported in 295 surveys conducted in PNG between 1990 and 2014, of which 65 used more than one test. Results from different diagnostics were standardised using a set of criteria that included a model to predict antigen prevalence from microfilariae prevalence. We mapped the point location of each of these surveys and categorised their standardised prevalence estimates. RESULTS: Several predictive models were produced and investigated, including the effect of any mass drug administration and number of rounds prior to the surveys. One model was chosen based on goodness of fit parameters and used to predict antigen prevalence for surveys that tested only for microfilariae. Standardised prevalence values show that 72% of all surveys reported a prevalence above 0.05. High prevalence was situated on the coastal north, south and island regions, while the central highland area of Papua New Guinea shows low levels of prevalence. CONCLUSIONS: Our study is the first to provide an explicit predictive relationship between the prevalence values based on empirical results from antigen and microfilaria tests, taking into account the occurrence of mass drug administration. This is a crucial step to combine studies to develop risk maps of lymphatic filariasis for programme planning and evaluation, as shown in the case of Papua New Guinea. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s41182-018-0123-8) contains supplementary material, which is available to authorized users. BioMed Central 2018-12-04 /pmc/articles/PMC6280391/ /pubmed/30533996 http://dx.doi.org/10.1186/s41182-018-0123-8 Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Berg Soto, Alvaro
Xu, Zhijing
Wood, Peter
Sanuku, Nelly
Robinson, Leanne J.
King, Christopher L.
Tisch, Daniel
Susapu, Melinda
Graves, Patricia M.
Combining different diagnostic studies of lymphatic filariasis for risk mapping in Papua New Guinea: a predictive model from microfilaraemia and antigenaemia prevalence surveys
title Combining different diagnostic studies of lymphatic filariasis for risk mapping in Papua New Guinea: a predictive model from microfilaraemia and antigenaemia prevalence surveys
title_full Combining different diagnostic studies of lymphatic filariasis for risk mapping in Papua New Guinea: a predictive model from microfilaraemia and antigenaemia prevalence surveys
title_fullStr Combining different diagnostic studies of lymphatic filariasis for risk mapping in Papua New Guinea: a predictive model from microfilaraemia and antigenaemia prevalence surveys
title_full_unstemmed Combining different diagnostic studies of lymphatic filariasis for risk mapping in Papua New Guinea: a predictive model from microfilaraemia and antigenaemia prevalence surveys
title_short Combining different diagnostic studies of lymphatic filariasis for risk mapping in Papua New Guinea: a predictive model from microfilaraemia and antigenaemia prevalence surveys
title_sort combining different diagnostic studies of lymphatic filariasis for risk mapping in papua new guinea: a predictive model from microfilaraemia and antigenaemia prevalence surveys
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6280391/
https://www.ncbi.nlm.nih.gov/pubmed/30533996
http://dx.doi.org/10.1186/s41182-018-0123-8
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