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Modernizing the design and analysis of prevalence surveys for neglected tropical diseases
Current WHO guidelines set prevalence thresholds below which a neglected tropical disease can be considered to have been eliminated as a public health problem, and specify how surveys to assess whether elimination has been achieved should be designed and analysed, based on classical survey sampling...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10440170/ https://www.ncbi.nlm.nih.gov/pubmed/37598704 http://dx.doi.org/10.1098/rstb.2022.0276 |
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author | Diggle, Peter J Fronterre, Claudio Gass, Katherine Hundley, Lee Niles-Robin, Reza Sampson, Annastacia Morice, Ana Scholte, Ronaldo Carvalho |
author_facet | Diggle, Peter J Fronterre, Claudio Gass, Katherine Hundley, Lee Niles-Robin, Reza Sampson, Annastacia Morice, Ana Scholte, Ronaldo Carvalho |
author_sort | Diggle, Peter J |
collection | PubMed |
description | Current WHO guidelines set prevalence thresholds below which a neglected tropical disease can be considered to have been eliminated as a public health problem, and specify how surveys to assess whether elimination has been achieved should be designed and analysed, based on classical survey sampling methods. In this paper, we describe an alternative approach based on geospatial statistical modelling. We first show the gains in efficiency that can be obtained by exploiting any spatial correlation in the underlying prevalence. We then suggest that the current guidelines' implicit use of a significance testing argument is not appropriate; instead, we argue for a predictive inferential framework, leading to design criteria based on controlling the rates at which areas whose true prevalence lies above and below the elimination threshold are incorrectly classified. We describe how this approach naturally accommodates context-specific information in the form of georeferenced covariates that have been shown to be predictive of disease prevalence. Finally, we give a progress report of an ongoing collaboration with the Guyana Ministry of Health Neglected Tropical Disease programme on the design of an IDA (ivermectin, diethylcarbamazine and albendazole) Impact Survey of lymphatic filariasis to be conducted in Guyana in early 2023. This article is part of the theme issue ‘Challenges and opportunities in the fight against neglected tropical diseases: a decade from the London Declaration on NTDs’. |
format | Online Article Text |
id | pubmed-10440170 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | The Royal Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-104401702023-08-21 Modernizing the design and analysis of prevalence surveys for neglected tropical diseases Diggle, Peter J Fronterre, Claudio Gass, Katherine Hundley, Lee Niles-Robin, Reza Sampson, Annastacia Morice, Ana Scholte, Ronaldo Carvalho Philos Trans R Soc Lond B Biol Sci Articles Current WHO guidelines set prevalence thresholds below which a neglected tropical disease can be considered to have been eliminated as a public health problem, and specify how surveys to assess whether elimination has been achieved should be designed and analysed, based on classical survey sampling methods. In this paper, we describe an alternative approach based on geospatial statistical modelling. We first show the gains in efficiency that can be obtained by exploiting any spatial correlation in the underlying prevalence. We then suggest that the current guidelines' implicit use of a significance testing argument is not appropriate; instead, we argue for a predictive inferential framework, leading to design criteria based on controlling the rates at which areas whose true prevalence lies above and below the elimination threshold are incorrectly classified. We describe how this approach naturally accommodates context-specific information in the form of georeferenced covariates that have been shown to be predictive of disease prevalence. Finally, we give a progress report of an ongoing collaboration with the Guyana Ministry of Health Neglected Tropical Disease programme on the design of an IDA (ivermectin, diethylcarbamazine and albendazole) Impact Survey of lymphatic filariasis to be conducted in Guyana in early 2023. This article is part of the theme issue ‘Challenges and opportunities in the fight against neglected tropical diseases: a decade from the London Declaration on NTDs’. The Royal Society 2023-10-09 2023-08-21 /pmc/articles/PMC10440170/ /pubmed/37598704 http://dx.doi.org/10.1098/rstb.2022.0276 Text en © 2023 The Authors. https://creativecommons.org/licenses/by/4.0/Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, provided the original author and source are credited. |
spellingShingle | Articles Diggle, Peter J Fronterre, Claudio Gass, Katherine Hundley, Lee Niles-Robin, Reza Sampson, Annastacia Morice, Ana Scholte, Ronaldo Carvalho Modernizing the design and analysis of prevalence surveys for neglected tropical diseases |
title | Modernizing the design and analysis of prevalence surveys for neglected tropical diseases |
title_full | Modernizing the design and analysis of prevalence surveys for neglected tropical diseases |
title_fullStr | Modernizing the design and analysis of prevalence surveys for neglected tropical diseases |
title_full_unstemmed | Modernizing the design and analysis of prevalence surveys for neglected tropical diseases |
title_short | Modernizing the design and analysis of prevalence surveys for neglected tropical diseases |
title_sort | modernizing the design and analysis of prevalence surveys for neglected tropical diseases |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10440170/ https://www.ncbi.nlm.nih.gov/pubmed/37598704 http://dx.doi.org/10.1098/rstb.2022.0276 |
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