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Bayesian Geostatistical Model-Based Estimates of Soil-Transmitted Helminth Infection in Nigeria, Including Annual Deworming Requirements

BACKGROUND: The acceleration of the control of soil-transmitted helminth (STH) infections in Nigeria, emphasizing preventive chemotherapy, has become imperative in light of the global fight against neglected tropical diseases. Predictive risk maps are an important tool to guide and support control a...

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Autores principales: Oluwole, Akinola S., Ekpo, Uwem F., Karagiannis-Voules, Dimitrios-Alexios, Abe, Eniola M., Olamiju, Francisca O., Isiyaku, Sunday, Okoronkwo, Chukwu, Saka, Yisa, Nebe, Obiageli J., Braide, Eka I., Mafiana, Chiedu F., Utzinger, Jürg, Vounatsou, Penelope
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4409219/
https://www.ncbi.nlm.nih.gov/pubmed/25909633
http://dx.doi.org/10.1371/journal.pntd.0003740
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author Oluwole, Akinola S.
Ekpo, Uwem F.
Karagiannis-Voules, Dimitrios-Alexios
Abe, Eniola M.
Olamiju, Francisca O.
Isiyaku, Sunday
Okoronkwo, Chukwu
Saka, Yisa
Nebe, Obiageli J.
Braide, Eka I.
Mafiana, Chiedu F.
Utzinger, Jürg
Vounatsou, Penelope
author_facet Oluwole, Akinola S.
Ekpo, Uwem F.
Karagiannis-Voules, Dimitrios-Alexios
Abe, Eniola M.
Olamiju, Francisca O.
Isiyaku, Sunday
Okoronkwo, Chukwu
Saka, Yisa
Nebe, Obiageli J.
Braide, Eka I.
Mafiana, Chiedu F.
Utzinger, Jürg
Vounatsou, Penelope
author_sort Oluwole, Akinola S.
collection PubMed
description BACKGROUND: The acceleration of the control of soil-transmitted helminth (STH) infections in Nigeria, emphasizing preventive chemotherapy, has become imperative in light of the global fight against neglected tropical diseases. Predictive risk maps are an important tool to guide and support control activities. METHODOLOGY: STH infection prevalence data were obtained from surveys carried out in 2011 using standard protocols. Data were geo-referenced and collated in a nationwide, geographic information system database. Bayesian geostatistical models with remotely sensed environmental covariates and variable selection procedures were utilized to predict the spatial distribution of STH infections in Nigeria. PRINCIPAL FINDINGS: We found that hookworm, Ascaris lumbricoides, and Trichuris trichiura infections are endemic in 482 (86.8%), 305 (55.0%), and 55 (9.9%) locations, respectively. Hookworm and A. lumbricoides infection co-exist in 16 states, while the three species are co-endemic in 12 states. Overall, STHs are endemic in 20 of the 36 states of Nigeria, including the Federal Capital Territory of Abuja. The observed prevalence at endemic locations ranged from 1.7% to 51.7% for hookworm, from 1.6% to 77.8% for A. lumbricoides, and from 1.0% to 25.5% for T. trichiura. Model-based predictions ranged from 0.7% to 51.0% for hookworm, from 0.1% to 82.6% for A. lumbricoides, and from 0.0% to 18.5% for T. trichiura. Our models suggest that day land surface temperature and dense vegetation are important predictors of the spatial distribution of STH infection in Nigeria. In 2011, a total of 5.7 million (13.8%) school-aged children were predicted to be infected with STHs in Nigeria. Mass treatment at the local government area level for annual or bi-annual treatment of the school-aged population in Nigeria in 2011, based on World Health Organization prevalence thresholds, were estimated at 10.2 million tablets. CONCLUSIONS/SIGNIFICANCE: The predictive risk maps and estimated deworming needs presented here will be helpful for escalating the control and spatial targeting of interventions against STH infections in Nigeria.
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spelling pubmed-44092192015-05-12 Bayesian Geostatistical Model-Based Estimates of Soil-Transmitted Helminth Infection in Nigeria, Including Annual Deworming Requirements Oluwole, Akinola S. Ekpo, Uwem F. Karagiannis-Voules, Dimitrios-Alexios Abe, Eniola M. Olamiju, Francisca O. Isiyaku, Sunday Okoronkwo, Chukwu Saka, Yisa Nebe, Obiageli J. Braide, Eka I. Mafiana, Chiedu F. Utzinger, Jürg Vounatsou, Penelope PLoS Negl Trop Dis Research Article BACKGROUND: The acceleration of the control of soil-transmitted helminth (STH) infections in Nigeria, emphasizing preventive chemotherapy, has become imperative in light of the global fight against neglected tropical diseases. Predictive risk maps are an important tool to guide and support control activities. METHODOLOGY: STH infection prevalence data were obtained from surveys carried out in 2011 using standard protocols. Data were geo-referenced and collated in a nationwide, geographic information system database. Bayesian geostatistical models with remotely sensed environmental covariates and variable selection procedures were utilized to predict the spatial distribution of STH infections in Nigeria. PRINCIPAL FINDINGS: We found that hookworm, Ascaris lumbricoides, and Trichuris trichiura infections are endemic in 482 (86.8%), 305 (55.0%), and 55 (9.9%) locations, respectively. Hookworm and A. lumbricoides infection co-exist in 16 states, while the three species are co-endemic in 12 states. Overall, STHs are endemic in 20 of the 36 states of Nigeria, including the Federal Capital Territory of Abuja. The observed prevalence at endemic locations ranged from 1.7% to 51.7% for hookworm, from 1.6% to 77.8% for A. lumbricoides, and from 1.0% to 25.5% for T. trichiura. Model-based predictions ranged from 0.7% to 51.0% for hookworm, from 0.1% to 82.6% for A. lumbricoides, and from 0.0% to 18.5% for T. trichiura. Our models suggest that day land surface temperature and dense vegetation are important predictors of the spatial distribution of STH infection in Nigeria. In 2011, a total of 5.7 million (13.8%) school-aged children were predicted to be infected with STHs in Nigeria. Mass treatment at the local government area level for annual or bi-annual treatment of the school-aged population in Nigeria in 2011, based on World Health Organization prevalence thresholds, were estimated at 10.2 million tablets. CONCLUSIONS/SIGNIFICANCE: The predictive risk maps and estimated deworming needs presented here will be helpful for escalating the control and spatial targeting of interventions against STH infections in Nigeria. Public Library of Science 2015-04-24 /pmc/articles/PMC4409219/ /pubmed/25909633 http://dx.doi.org/10.1371/journal.pntd.0003740 Text en © 2015 Oluwole 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
Oluwole, Akinola S.
Ekpo, Uwem F.
Karagiannis-Voules, Dimitrios-Alexios
Abe, Eniola M.
Olamiju, Francisca O.
Isiyaku, Sunday
Okoronkwo, Chukwu
Saka, Yisa
Nebe, Obiageli J.
Braide, Eka I.
Mafiana, Chiedu F.
Utzinger, Jürg
Vounatsou, Penelope
Bayesian Geostatistical Model-Based Estimates of Soil-Transmitted Helminth Infection in Nigeria, Including Annual Deworming Requirements
title Bayesian Geostatistical Model-Based Estimates of Soil-Transmitted Helminth Infection in Nigeria, Including Annual Deworming Requirements
title_full Bayesian Geostatistical Model-Based Estimates of Soil-Transmitted Helminth Infection in Nigeria, Including Annual Deworming Requirements
title_fullStr Bayesian Geostatistical Model-Based Estimates of Soil-Transmitted Helminth Infection in Nigeria, Including Annual Deworming Requirements
title_full_unstemmed Bayesian Geostatistical Model-Based Estimates of Soil-Transmitted Helminth Infection in Nigeria, Including Annual Deworming Requirements
title_short Bayesian Geostatistical Model-Based Estimates of Soil-Transmitted Helminth Infection in Nigeria, Including Annual Deworming Requirements
title_sort bayesian geostatistical model-based estimates of soil-transmitted helminth infection in nigeria, including annual deworming requirements
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4409219/
https://www.ncbi.nlm.nih.gov/pubmed/25909633
http://dx.doi.org/10.1371/journal.pntd.0003740
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