Spatio-temporal distribution of soil-transmitted helminth infections in Brazil

被引:39
作者
Chammartin, Frederique [1 ,2 ]
Guimaraes, Luiz H. [3 ]
Scholte, Ronaldo G. C. [4 ]
Bavia, Mara E. [5 ]
Utzinger, Juerg [1 ,2 ]
Vounatsou, Penelope [1 ,2 ]
机构
[1] Swiss Trop & Publ Hlth Inst, Dept Epidemiol & Publ Hlth, CH-4002 Basel, Switzerland
[2] Univ Basel, CH-4003 Basel, Switzerland
[3] Univ Fed Bahia, Hosp Edgard Santos, Serv Immunol, BR-40110160 Salvador, BA, Brazil
[4] Secretaria Vigilancia Saude, BR-70304000 Brasilia, DF, Brazil
[5] Univ Fed Bahia, Dept Prevent Med, BR-40110060 Salvador, BA, Brazil
关键词
Soil-transmitted helminth; Ascaris lumbricoides; Hookworm; Trichuris trichiura; Predictive risk mapping; Bayesian geostatistics; Spatio-temporal model; Brazil; NEGLECTED TROPICAL DISEASES; SPATIAL-ANALYSIS; RISK; POPULATION; SELECTION; MODELS; DRUGS; WORMS;
D O I
10.1186/1756-3305-7-440
中图分类号
R38 [医学寄生虫学]; Q [生物科学];
学科分类号
07 ; 0710 ; 09 ; 100103 ;
摘要
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.
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页数:16
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