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Development and Assessment of a Geographic Knowledge-Based Model for Mapping Suitable Areas for Rift Valley Fever Transmission in Eastern Africa

Rift Valley fever (RVF), a mosquito-borne disease affecting ruminants and humans, is one of the most important viral zoonoses in Africa. The objective of the present study was to develop a geographic knowledge-based method to map the areas suitable for RVF amplification and RVF spread in four East A...

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Autores principales: Tran, Annelise, Trevennec, Carlène, Lutwama, Julius, Sserugga, Joseph, Gély, Marie, Pittiglio, Claudia, Pinto, Julio, Chevalier, Véronique
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5025187/
https://www.ncbi.nlm.nih.gov/pubmed/27631374
http://dx.doi.org/10.1371/journal.pntd.0004999
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author Tran, Annelise
Trevennec, Carlène
Lutwama, Julius
Sserugga, Joseph
Gély, Marie
Pittiglio, Claudia
Pinto, Julio
Chevalier, Véronique
author_facet Tran, Annelise
Trevennec, Carlène
Lutwama, Julius
Sserugga, Joseph
Gély, Marie
Pittiglio, Claudia
Pinto, Julio
Chevalier, Véronique
author_sort Tran, Annelise
collection PubMed
description Rift Valley fever (RVF), a mosquito-borne disease affecting ruminants and humans, is one of the most important viral zoonoses in Africa. The objective of the present study was to develop a geographic knowledge-based method to map the areas suitable for RVF amplification and RVF spread in four East African countries, namely, Kenya, Tanzania, Uganda and Ethiopia, and to assess the predictive accuracy of the model using livestock outbreak data from Kenya and Tanzania. Risk factors and their relative importance regarding RVF amplification and spread were identified from a literature review. A numerical weight was calculated for each risk factor using an analytical hierarchy process. The corresponding geographic data were collected, standardized and combined based on a weighted linear combination to produce maps of the suitability for RVF transmission. The accuracy of the resulting maps was assessed using RVF outbreak locations in livestock reported in Kenya and Tanzania between 1998 and 2012 and the ROC curve analysis. Our results confirmed the capacity of the geographic information system-based multi-criteria evaluation method to synthesize available scientific knowledge and to accurately map (AUC = 0.786; 95% CI [0.730–0.842]) the spatial heterogeneity of RVF suitability in East Africa. This approach provides users with a straightforward and easy update of the maps according to data availability or the further development of scientific knowledge.
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spelling pubmed-50251872016-09-27 Development and Assessment of a Geographic Knowledge-Based Model for Mapping Suitable Areas for Rift Valley Fever Transmission in Eastern Africa Tran, Annelise Trevennec, Carlène Lutwama, Julius Sserugga, Joseph Gély, Marie Pittiglio, Claudia Pinto, Julio Chevalier, Véronique PLoS Negl Trop Dis Research Article Rift Valley fever (RVF), a mosquito-borne disease affecting ruminants and humans, is one of the most important viral zoonoses in Africa. The objective of the present study was to develop a geographic knowledge-based method to map the areas suitable for RVF amplification and RVF spread in four East African countries, namely, Kenya, Tanzania, Uganda and Ethiopia, and to assess the predictive accuracy of the model using livestock outbreak data from Kenya and Tanzania. Risk factors and their relative importance regarding RVF amplification and spread were identified from a literature review. A numerical weight was calculated for each risk factor using an analytical hierarchy process. The corresponding geographic data were collected, standardized and combined based on a weighted linear combination to produce maps of the suitability for RVF transmission. The accuracy of the resulting maps was assessed using RVF outbreak locations in livestock reported in Kenya and Tanzania between 1998 and 2012 and the ROC curve analysis. Our results confirmed the capacity of the geographic information system-based multi-criteria evaluation method to synthesize available scientific knowledge and to accurately map (AUC = 0.786; 95% CI [0.730–0.842]) the spatial heterogeneity of RVF suitability in East Africa. This approach provides users with a straightforward and easy update of the maps according to data availability or the further development of scientific knowledge. Public Library of Science 2016-09-15 /pmc/articles/PMC5025187/ /pubmed/27631374 http://dx.doi.org/10.1371/journal.pntd.0004999 Text en © 2016 Tran 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 (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Tran, Annelise
Trevennec, Carlène
Lutwama, Julius
Sserugga, Joseph
Gély, Marie
Pittiglio, Claudia
Pinto, Julio
Chevalier, Véronique
Development and Assessment of a Geographic Knowledge-Based Model for Mapping Suitable Areas for Rift Valley Fever Transmission in Eastern Africa
title Development and Assessment of a Geographic Knowledge-Based Model for Mapping Suitable Areas for Rift Valley Fever Transmission in Eastern Africa
title_full Development and Assessment of a Geographic Knowledge-Based Model for Mapping Suitable Areas for Rift Valley Fever Transmission in Eastern Africa
title_fullStr Development and Assessment of a Geographic Knowledge-Based Model for Mapping Suitable Areas for Rift Valley Fever Transmission in Eastern Africa
title_full_unstemmed Development and Assessment of a Geographic Knowledge-Based Model for Mapping Suitable Areas for Rift Valley Fever Transmission in Eastern Africa
title_short Development and Assessment of a Geographic Knowledge-Based Model for Mapping Suitable Areas for Rift Valley Fever Transmission in Eastern Africa
title_sort development and assessment of a geographic knowledge-based model for mapping suitable areas for rift valley fever transmission in eastern africa
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5025187/
https://www.ncbi.nlm.nih.gov/pubmed/27631374
http://dx.doi.org/10.1371/journal.pntd.0004999
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