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Determining Treatment Needs at Different Spatial Scales Using Geostatistical Model-Based Risk Estimates of Schistosomiasis
BACKGROUND: After many years of neglect, schistosomiasis control is going to scale. The strategy of choice is preventive chemotherapy, that is the repeated large-scale administration of praziquantel (a safe and highly efficacious drug) to at-risk populations. The frequency of praziquantel administra...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3441409/ https://www.ncbi.nlm.nih.gov/pubmed/23029570 http://dx.doi.org/10.1371/journal.pntd.0001773 |
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author | Schur, Nadine Vounatsou, Penelope Utzinger, Jürg |
author_facet | Schur, Nadine Vounatsou, Penelope Utzinger, Jürg |
author_sort | Schur, Nadine |
collection | PubMed |
description | BACKGROUND: After many years of neglect, schistosomiasis control is going to scale. The strategy of choice is preventive chemotherapy, that is the repeated large-scale administration of praziquantel (a safe and highly efficacious drug) to at-risk populations. The frequency of praziquantel administration is based on endemicity, which usually is defined by prevalence data summarized at an arbitrarily chosen administrative level. METHODOLOGY: For an ensemble of 29 West and East African countries, we determined the annualized praziquantel treatment needs for the school-aged population, adhering to World Health Organization guidelines. Different administrative levels of prevalence aggregation were considered; country, province, district, and pixel level. Previously published results on spatially explicit schistosomiasis risk in the selected countries were employed to classify each area into distinct endemicity classes that govern the frequency of praziquantel administration. PRINCIPAL FINDINGS: Estimates of infection prevalence adjusted for the school-aged population in 2010 revealed that most countries are classified as moderately endemic for schistosomiasis (prevalence 10–50%), while four countries (i.e., Ghana, Liberia, Mozambique, and Sierra Leone) are highly endemic (>50%). Overall, 72.7 million annualized praziquantel treatments (50% confidence interval (CI): 68.8–100.7 million) are required for the school-aged population if country-level schistosomiasis prevalence estimates are considered, and 81.5 million treatments (50% CI: 67.3–107.5 million) if estimation is based on a more refined spatial scale at the provincial level. CONCLUSIONS/SIGNIFICANCE: Praziquantel treatment needs may be over- or underestimated depending on the level of spatial aggregation. The distribution of schistosomiasis in Ethiopia, Liberia, Mauritania, Uganda, and Zambia is rather uniform, and hence country-level risk estimates are sufficient to calculate treatment needs. On the other hand, countries like Burkina Faso, Mali, Mozambique, Sudan, and Tanzania show large spatial heterogeneity in schistosomiasis risk, which should be taken into account for calculating treatment requirements. |
format | Online Article Text |
id | pubmed-3441409 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-34414092012-10-01 Determining Treatment Needs at Different Spatial Scales Using Geostatistical Model-Based Risk Estimates of Schistosomiasis Schur, Nadine Vounatsou, Penelope Utzinger, Jürg PLoS Negl Trop Dis Research Article BACKGROUND: After many years of neglect, schistosomiasis control is going to scale. The strategy of choice is preventive chemotherapy, that is the repeated large-scale administration of praziquantel (a safe and highly efficacious drug) to at-risk populations. The frequency of praziquantel administration is based on endemicity, which usually is defined by prevalence data summarized at an arbitrarily chosen administrative level. METHODOLOGY: For an ensemble of 29 West and East African countries, we determined the annualized praziquantel treatment needs for the school-aged population, adhering to World Health Organization guidelines. Different administrative levels of prevalence aggregation were considered; country, province, district, and pixel level. Previously published results on spatially explicit schistosomiasis risk in the selected countries were employed to classify each area into distinct endemicity classes that govern the frequency of praziquantel administration. PRINCIPAL FINDINGS: Estimates of infection prevalence adjusted for the school-aged population in 2010 revealed that most countries are classified as moderately endemic for schistosomiasis (prevalence 10–50%), while four countries (i.e., Ghana, Liberia, Mozambique, and Sierra Leone) are highly endemic (>50%). Overall, 72.7 million annualized praziquantel treatments (50% confidence interval (CI): 68.8–100.7 million) are required for the school-aged population if country-level schistosomiasis prevalence estimates are considered, and 81.5 million treatments (50% CI: 67.3–107.5 million) if estimation is based on a more refined spatial scale at the provincial level. CONCLUSIONS/SIGNIFICANCE: Praziquantel treatment needs may be over- or underestimated depending on the level of spatial aggregation. The distribution of schistosomiasis in Ethiopia, Liberia, Mauritania, Uganda, and Zambia is rather uniform, and hence country-level risk estimates are sufficient to calculate treatment needs. On the other hand, countries like Burkina Faso, Mali, Mozambique, Sudan, and Tanzania show large spatial heterogeneity in schistosomiasis risk, which should be taken into account for calculating treatment requirements. Public Library of Science 2012-09-13 /pmc/articles/PMC3441409/ /pubmed/23029570 http://dx.doi.org/10.1371/journal.pntd.0001773 Text en © 2012 Schur 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 Schur, Nadine Vounatsou, Penelope Utzinger, Jürg Determining Treatment Needs at Different Spatial Scales Using Geostatistical Model-Based Risk Estimates of Schistosomiasis |
title | Determining Treatment Needs at Different Spatial Scales Using Geostatistical Model-Based Risk Estimates of Schistosomiasis |
title_full | Determining Treatment Needs at Different Spatial Scales Using Geostatistical Model-Based Risk Estimates of Schistosomiasis |
title_fullStr | Determining Treatment Needs at Different Spatial Scales Using Geostatistical Model-Based Risk Estimates of Schistosomiasis |
title_full_unstemmed | Determining Treatment Needs at Different Spatial Scales Using Geostatistical Model-Based Risk Estimates of Schistosomiasis |
title_short | Determining Treatment Needs at Different Spatial Scales Using Geostatistical Model-Based Risk Estimates of Schistosomiasis |
title_sort | determining treatment needs at different spatial scales using geostatistical model-based risk estimates of schistosomiasis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3441409/ https://www.ncbi.nlm.nih.gov/pubmed/23029570 http://dx.doi.org/10.1371/journal.pntd.0001773 |
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