Literature DB >> 17716433

Spatial modelling and the prediction of Loa loa risk: decision making under uncertainty.

P J Diggle1, M C Thomson, O F Christensen, B Rowlingson, V Obsomer, J Gardon, S Wanji, I Takougang, P Enyong, J Kamgno, J H Remme, M Boussinesq, D H Molyneux.   

Abstract

Health decision-makers working in Africa often need to act for millions of people over large geographical areas on little and uncertain information. Spatial statistical modelling and Bayesian inference have now been used to quantify the uncertainty in the predictions of a regional, environmental risk map for Loa loa (a map that is currently being used as an essential decision tool by the African Programme for Onchocerciasis Control). The methodology allows the expression of the probability that, given the data, a particular location does or does not exceed a predefined high-risk threshold for which a change in strategy for the delivery of the antihelmintic ivermectin is required.

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Year:  2007        PMID: 17716433     DOI: 10.1179/136485913X13789813917463

Source DB:  PubMed          Journal:  Ann Trop Med Parasitol        ISSN: 0003-4983


  44 in total

1.  Loss Function Based Ranking in Two-Stage, Hierarchical Models.

Authors:  Rongheng Lin; Thomas A Louis; Susan M Paddock; Greg Ridgeway
Journal:  Bayesian Anal       Date:  2006-01-01       Impact factor: 3.728

2.  Bayesian geostatistics in health cartography: the perspective of malaria.

Authors:  Anand P Patil; Peter W Gething; Frédéric B Piel; Simon I Hay
Journal:  Trends Parasitol       Date:  2011-03-17

3.  Spatio-temporal patterns of schistosomiasis japonica in lake and marshland areas in China: the effect of snail habitats.

Authors:  Yi Hu; Jie Gao; Meina Chi; Can Luo; Henry Lynn; Liqian Sun; Bo Tao; Decheng Wang; Zhijie Zhang; Qingwu Jiang
Journal:  Am J Trop Med Hyg       Date:  2014-06-30       Impact factor: 2.345

4.  Quantifying aggregated uncertainty in Plasmodium falciparum malaria prevalence and populations at risk via efficient space-time geostatistical joint simulation.

Authors:  Peter W Gething; Anand P Patil; Simon I Hay
Journal:  PLoS Comput Biol       Date:  2010-04-01       Impact factor: 4.475

5.  Targeting trachoma control through risk mapping: the example of Southern Sudan.

Authors:  Archie C A Clements; Lucia W Kur; Gideon Gatpan; Jeremiah M Ngondi; Paul M Emerson; Mounir Lado; Anthony Sabasio; Jan H Kolaczinski
Journal:  PLoS Negl Trop Dis       Date:  2010-08-17

Review 6.  Rapid mapping of schistosomiasis and other neglected tropical diseases in the context of integrated control programmes in Africa.

Authors:  S Brooker; N B Kabatereine; J O Gyapong; J R Stothard; J Utzinger
Journal:  Parasitology       Date:  2009-05-19       Impact factor: 3.234

7.  Bayesian risk maps for Schistosoma mansoni and hookworm mono-infections in a setting where both parasites co-exist.

Authors:  Giovanna Raso; Penelope Vounatsou; Donald P McManus; Jürg Utzinger
Journal:  Geospat Health       Date:  2007-11       Impact factor: 1.212

8.  A world malaria map: Plasmodium falciparum endemicity in 2007.

Authors:  Simon I Hay; Carlos A Guerra; Peter W Gething; Anand P Patil; Andrew J Tatem; Abdisalan M Noor; Caroline W Kabaria; Bui H Manh; Iqbal R F Elyazar; Simon Brooker; David L Smith; Rana A Moyeed; Robert W Snow
Journal:  PLoS Med       Date:  2009-03-24       Impact factor: 11.069

9.  A comparative study of the spatial distribution of schistosomiasis in Mali in 1984-1989 and 2004-2006.

Authors:  Archie C A Clements; Elisa Bosqué-Oliva; Moussa Sacko; Aly Landouré; Robert Dembélé; Mamadou Traoré; Godefroy Coulibaly; Albis F Gabrielli; Alan Fenwick; Simon Brooker
Journal:  PLoS Negl Trop Dis       Date:  2009-05-05

10.  Spatial heterogeneity of parasite co-infection: Determinants and geostatistical prediction at regional scales.

Authors:  Simon Brooker; Archie C A Clements
Journal:  Int J Parasitol       Date:  2008-12-03       Impact factor: 3.981

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