Cargando…
Spatio-temporal distribution of soil-transmitted helminth infections in Brazil
BACKGROUND: In Brazil, preventive chemotherapy targeting soil-transmitted helminthiasis is being scaled-up. Hence, spatially explicit estimates of infection risks providing information about the current situation are needed to guide interventions. Available high-resolution national model-based estim...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4262198/ https://www.ncbi.nlm.nih.gov/pubmed/25230810 http://dx.doi.org/10.1186/1756-3305-7-440 |
_version_ | 1782348394229923840 |
---|---|
author | Chammartin, Frédérique Guimarães, Luiz H Scholte, Ronaldo GC Bavia, Mara E Utzinger, Jürg Vounatsou, Penelope |
author_facet | Chammartin, Frédérique Guimarães, Luiz H Scholte, Ronaldo GC Bavia, Mara E Utzinger, Jürg Vounatsou, Penelope |
author_sort | Chammartin, Frédérique |
collection | PubMed |
description | BACKGROUND: In Brazil, preventive chemotherapy targeting soil-transmitted helminthiasis is being scaled-up. Hence, spatially explicit estimates of infection risks providing information about the current situation are needed to guide interventions. Available high-resolution national model-based estimates either rely on analyses of data restricted to a given period of time, or on historical data collected over a longer period. While efforts have been made to take into account the spatial structure of the data in the modelling approach, little emphasis has been placed on the temporal dimension. METHODS: We extracted georeferenced survey data on the prevalence of infection with soil-transmitted helminths (i.e. Ascaris lumbricoides, hookworm and Trichuris trichiura) in Brazil from the Global Neglected Tropical Diseases (GNTD) database. Selection of the most important predictors of infection risk was carried out using a Bayesian geostatistical approach and temporal models that address non-linearity and correlation of the explanatory variables. The spatial process was estimated through a predictive process approximation. Spatio-temporal models were built on the selected predictors with integrated nested Laplace approximation using stochastic partial differential equations. RESULTS: Our models revealed that, over the past 20 years, the risk of soil-transmitted helminth infection has decreased in Brazil, mainly because of the reduction of A. lumbricoides and hookworm infections. From 2010 onwards, we estimate that the infection prevalences with A. lumbricoides, hookworm and T. trichiura are 3.6%, 1.7% and 1.4%, respectively. We also provide a map highlighting municipalities in need of preventive chemotherapy, based on a predicted soil-transmitted helminth infection risk in excess of 20%. The need for treatments in the school-aged population at the municipality level was estimated at 1.8 million doses of anthelminthic tablets per year. CONCLUSIONS: The analysis of the spatio-temporal aspect of the risk of infection with soil-transmitted helminths contributes to a better understanding of the evolution of risk over time. Risk estimates provide the soil-transmitted helminthiasis control programme in Brazil with useful benchmark information for prioritising and improving spatial and temporal targeting of interventions. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1756-3305-7-440) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4262198 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-42621982014-12-11 Spatio-temporal distribution of soil-transmitted helminth infections in Brazil Chammartin, Frédérique Guimarães, Luiz H Scholte, Ronaldo GC Bavia, Mara E Utzinger, Jürg Vounatsou, Penelope Parasit Vectors Research BACKGROUND: In Brazil, preventive chemotherapy targeting soil-transmitted helminthiasis is being scaled-up. Hence, spatially explicit estimates of infection risks providing information about the current situation are needed to guide interventions. Available high-resolution national model-based estimates either rely on analyses of data restricted to a given period of time, or on historical data collected over a longer period. While efforts have been made to take into account the spatial structure of the data in the modelling approach, little emphasis has been placed on the temporal dimension. METHODS: We extracted georeferenced survey data on the prevalence of infection with soil-transmitted helminths (i.e. Ascaris lumbricoides, hookworm and Trichuris trichiura) in Brazil from the Global Neglected Tropical Diseases (GNTD) database. Selection of the most important predictors of infection risk was carried out using a Bayesian geostatistical approach and temporal models that address non-linearity and correlation of the explanatory variables. The spatial process was estimated through a predictive process approximation. Spatio-temporal models were built on the selected predictors with integrated nested Laplace approximation using stochastic partial differential equations. RESULTS: Our models revealed that, over the past 20 years, the risk of soil-transmitted helminth infection has decreased in Brazil, mainly because of the reduction of A. lumbricoides and hookworm infections. From 2010 onwards, we estimate that the infection prevalences with A. lumbricoides, hookworm and T. trichiura are 3.6%, 1.7% and 1.4%, respectively. We also provide a map highlighting municipalities in need of preventive chemotherapy, based on a predicted soil-transmitted helminth infection risk in excess of 20%. The need for treatments in the school-aged population at the municipality level was estimated at 1.8 million doses of anthelminthic tablets per year. CONCLUSIONS: The analysis of the spatio-temporal aspect of the risk of infection with soil-transmitted helminths contributes to a better understanding of the evolution of risk over time. Risk estimates provide the soil-transmitted helminthiasis control programme in Brazil with useful benchmark information for prioritising and improving spatial and temporal targeting of interventions. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1756-3305-7-440) contains supplementary material, which is available to authorized users. BioMed Central 2014-09-18 /pmc/articles/PMC4262198/ /pubmed/25230810 http://dx.doi.org/10.1186/1756-3305-7-440 Text en © Chammartin et al.; licensee BioMed Central Ltd. 2014 This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. 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 Chammartin, Frédérique Guimarães, Luiz H Scholte, Ronaldo GC Bavia, Mara E Utzinger, Jürg Vounatsou, Penelope Spatio-temporal distribution of soil-transmitted helminth infections in Brazil |
title | Spatio-temporal distribution of soil-transmitted helminth infections in Brazil |
title_full | Spatio-temporal distribution of soil-transmitted helminth infections in Brazil |
title_fullStr | Spatio-temporal distribution of soil-transmitted helminth infections in Brazil |
title_full_unstemmed | Spatio-temporal distribution of soil-transmitted helminth infections in Brazil |
title_short | Spatio-temporal distribution of soil-transmitted helminth infections in Brazil |
title_sort | spatio-temporal distribution of soil-transmitted helminth infections in brazil |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4262198/ https://www.ncbi.nlm.nih.gov/pubmed/25230810 http://dx.doi.org/10.1186/1756-3305-7-440 |
work_keys_str_mv | AT chammartinfrederique spatiotemporaldistributionofsoiltransmittedhelminthinfectionsinbrazil AT guimaraesluizh spatiotemporaldistributionofsoiltransmittedhelminthinfectionsinbrazil AT scholteronaldogc spatiotemporaldistributionofsoiltransmittedhelminthinfectionsinbrazil AT baviamarae spatiotemporaldistributionofsoiltransmittedhelminthinfectionsinbrazil AT utzingerjurg spatiotemporaldistributionofsoiltransmittedhelminthinfectionsinbrazil AT vounatsoupenelope spatiotemporaldistributionofsoiltransmittedhelminthinfectionsinbrazil |