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Evaluating survey designs for targeting preventive chemotherapy against Schistosoma haematobium and Schistosoma mansoni across sub-Saharan Africa: a geostatistical analysis and modelling study

BACKGROUND: Schistosomiasis control programmes primarily use school-based surveys to identify areas for mass drug administration of preventive chemotherapy. However, as the spatial distribution of schistosomiasis can be highly focal, transmission may not be detected by surveys implemented at distric...

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Autores principales: Fornace, Kimberly M, Fronterrè, Claudio, Fleming, Fiona M., Simpson, Hope, Zoure, Honorat, Rebollo, Maria, Mwinzi, Pauline, Vounatsou, Penelope, Pullan, Rachel L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7672864/
https://www.ncbi.nlm.nih.gov/pubmed/33203463
http://dx.doi.org/10.1186/s13071-020-04413-7
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author Fornace, Kimberly M
Fronterrè, Claudio
Fleming, Fiona M.
Simpson, Hope
Zoure, Honorat
Rebollo, Maria
Mwinzi, Pauline
Vounatsou, Penelope
Pullan, Rachel L.
author_facet Fornace, Kimberly M
Fronterrè, Claudio
Fleming, Fiona M.
Simpson, Hope
Zoure, Honorat
Rebollo, Maria
Mwinzi, Pauline
Vounatsou, Penelope
Pullan, Rachel L.
author_sort Fornace, Kimberly M
collection PubMed
description BACKGROUND: Schistosomiasis control programmes primarily use school-based surveys to identify areas for mass drug administration of preventive chemotherapy. However, as the spatial distribution of schistosomiasis can be highly focal, transmission may not be detected by surveys implemented at districts or larger spatial units. Improved mapping strategies are required to accurately and cost-effectively target preventive chemotherapy to remaining foci across all possible spatial distributions of schistosomiasis. METHODS: Here, we use geostatistical models to quantify the spatial heterogeneity of Schistosoma haematobium and S. mansoni across sub-Saharan Africa using the most comprehensive dataset available on school-based surveys. Applying this information to parameterise simulations, we assess the accuracy and cost of targeting alternative implementation unit sizes across the range of plausible schistosomiasis distributions. We evaluate the consequences of decisions based on survey designs implemented at district and subdistrict levels sampling different numbers of schools. Cost data were obtained from field surveys conducted across multiple countries and years, with cost effectiveness evaluated as the cost per correctly identified school. RESULTS: Models identified marked differences in prevalence and spatial distributions between countries and species; however, results suggest implementing surveys at subdistrict level increase the accuracy of treatment classifications across most scenarios. While sampling intensively at the subdistrict level resulted in the highest classification accuracy, this sampling strategy resulted in the highest costs. Alternatively, sampling the same numbers of schools currently recommended at the district level but stratifying by subdistrict increased cost effectiveness. CONCLUSIONS: This study provides a new tool to evaluate schistosomiasis survey designs across a range of transmission settings. Results highlight the importance of considering spatial structure when designing sampling strategies, illustrating that a substantial proportion of children may be undertreated even when an implementation unit is correctly classified. Control programmes need to weigh the increased accuracy of more detailed mapping strategies against the survey costs and treatment priorities. [Image: see text]
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spelling pubmed-76728642020-11-19 Evaluating survey designs for targeting preventive chemotherapy against Schistosoma haematobium and Schistosoma mansoni across sub-Saharan Africa: a geostatistical analysis and modelling study Fornace, Kimberly M Fronterrè, Claudio Fleming, Fiona M. Simpson, Hope Zoure, Honorat Rebollo, Maria Mwinzi, Pauline Vounatsou, Penelope Pullan, Rachel L. Parasit Vectors Research BACKGROUND: Schistosomiasis control programmes primarily use school-based surveys to identify areas for mass drug administration of preventive chemotherapy. However, as the spatial distribution of schistosomiasis can be highly focal, transmission may not be detected by surveys implemented at districts or larger spatial units. Improved mapping strategies are required to accurately and cost-effectively target preventive chemotherapy to remaining foci across all possible spatial distributions of schistosomiasis. METHODS: Here, we use geostatistical models to quantify the spatial heterogeneity of Schistosoma haematobium and S. mansoni across sub-Saharan Africa using the most comprehensive dataset available on school-based surveys. Applying this information to parameterise simulations, we assess the accuracy and cost of targeting alternative implementation unit sizes across the range of plausible schistosomiasis distributions. We evaluate the consequences of decisions based on survey designs implemented at district and subdistrict levels sampling different numbers of schools. Cost data were obtained from field surveys conducted across multiple countries and years, with cost effectiveness evaluated as the cost per correctly identified school. RESULTS: Models identified marked differences in prevalence and spatial distributions between countries and species; however, results suggest implementing surveys at subdistrict level increase the accuracy of treatment classifications across most scenarios. While sampling intensively at the subdistrict level resulted in the highest classification accuracy, this sampling strategy resulted in the highest costs. Alternatively, sampling the same numbers of schools currently recommended at the district level but stratifying by subdistrict increased cost effectiveness. CONCLUSIONS: This study provides a new tool to evaluate schistosomiasis survey designs across a range of transmission settings. Results highlight the importance of considering spatial structure when designing sampling strategies, illustrating that a substantial proportion of children may be undertreated even when an implementation unit is correctly classified. Control programmes need to weigh the increased accuracy of more detailed mapping strategies against the survey costs and treatment priorities. [Image: see text] BioMed Central 2020-11-18 /pmc/articles/PMC7672864/ /pubmed/33203463 http://dx.doi.org/10.1186/s13071-020-04413-7 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data.
spellingShingle Research
Fornace, Kimberly M
Fronterrè, Claudio
Fleming, Fiona M.
Simpson, Hope
Zoure, Honorat
Rebollo, Maria
Mwinzi, Pauline
Vounatsou, Penelope
Pullan, Rachel L.
Evaluating survey designs for targeting preventive chemotherapy against Schistosoma haematobium and Schistosoma mansoni across sub-Saharan Africa: a geostatistical analysis and modelling study
title Evaluating survey designs for targeting preventive chemotherapy against Schistosoma haematobium and Schistosoma mansoni across sub-Saharan Africa: a geostatistical analysis and modelling study
title_full Evaluating survey designs for targeting preventive chemotherapy against Schistosoma haematobium and Schistosoma mansoni across sub-Saharan Africa: a geostatistical analysis and modelling study
title_fullStr Evaluating survey designs for targeting preventive chemotherapy against Schistosoma haematobium and Schistosoma mansoni across sub-Saharan Africa: a geostatistical analysis and modelling study
title_full_unstemmed Evaluating survey designs for targeting preventive chemotherapy against Schistosoma haematobium and Schistosoma mansoni across sub-Saharan Africa: a geostatistical analysis and modelling study
title_short Evaluating survey designs for targeting preventive chemotherapy against Schistosoma haematobium and Schistosoma mansoni across sub-Saharan Africa: a geostatistical analysis and modelling study
title_sort evaluating survey designs for targeting preventive chemotherapy against schistosoma haematobium and schistosoma mansoni across sub-saharan africa: a geostatistical analysis and modelling study
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7672864/
https://www.ncbi.nlm.nih.gov/pubmed/33203463
http://dx.doi.org/10.1186/s13071-020-04413-7
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