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Spatial epidemiology of human schistosomiasis in Africa: risk models, transmission dynamics and control()

This paper reviews recent studies on the spatial epidemiology of human schistosomiasis in Africa. The integrated use of geographical information systems, remote sensing and geostatistics has provided new insights into the ecology and epidemiology of schistosomiasis at a variety of spatial scales. Be...

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Detalles Bibliográficos
Autor principal: Brooker, Simon
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1975763/
https://www.ncbi.nlm.nih.gov/pubmed/17055547
http://dx.doi.org/10.1016/j.trstmh.2006.08.004
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author Brooker, Simon
author_facet Brooker, Simon
author_sort Brooker, Simon
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description This paper reviews recent studies on the spatial epidemiology of human schistosomiasis in Africa. The integrated use of geographical information systems, remote sensing and geostatistics has provided new insights into the ecology and epidemiology of schistosomiasis at a variety of spatial scales. Because large-scale patterns of transmission are influenced by climatic conditions, an increasing number of studies have used remotely sensed environmental data to predict spatial distributions, most recently using Bayesian methods of inference. Such data-driven approaches allow for a more rational implementation of intervention strategies across the continent. It is suggested that improved incorporation of transmission dynamics into spatial models and assessment of uncertainties inherent in data and modelling approaches represent important future research directions.
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spelling pubmed-19757632007-09-11 Spatial epidemiology of human schistosomiasis in Africa: risk models, transmission dynamics and control() Brooker, Simon Trans R Soc Trop Med Hyg Society Meeting Paper This paper reviews recent studies on the spatial epidemiology of human schistosomiasis in Africa. The integrated use of geographical information systems, remote sensing and geostatistics has provided new insights into the ecology and epidemiology of schistosomiasis at a variety of spatial scales. Because large-scale patterns of transmission are influenced by climatic conditions, an increasing number of studies have used remotely sensed environmental data to predict spatial distributions, most recently using Bayesian methods of inference. Such data-driven approaches allow for a more rational implementation of intervention strategies across the continent. It is suggested that improved incorporation of transmission dynamics into spatial models and assessment of uncertainties inherent in data and modelling approaches represent important future research directions. Oxford University Press 2007-01 /pmc/articles/PMC1975763/ /pubmed/17055547 http://dx.doi.org/10.1016/j.trstmh.2006.08.004 Text en © 2007 Elsevier Ltd. https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use.
spellingShingle Society Meeting Paper
Brooker, Simon
Spatial epidemiology of human schistosomiasis in Africa: risk models, transmission dynamics and control()
title Spatial epidemiology of human schistosomiasis in Africa: risk models, transmission dynamics and control()
title_full Spatial epidemiology of human schistosomiasis in Africa: risk models, transmission dynamics and control()
title_fullStr Spatial epidemiology of human schistosomiasis in Africa: risk models, transmission dynamics and control()
title_full_unstemmed Spatial epidemiology of human schistosomiasis in Africa: risk models, transmission dynamics and control()
title_short Spatial epidemiology of human schistosomiasis in Africa: risk models, transmission dynamics and control()
title_sort spatial epidemiology of human schistosomiasis in africa: risk models, transmission dynamics and control()
topic Society Meeting Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1975763/
https://www.ncbi.nlm.nih.gov/pubmed/17055547
http://dx.doi.org/10.1016/j.trstmh.2006.08.004
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