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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.
Tran, Annelise; Trevennec, Carlène; Lutwama, Julius; Sserugga, Joseph; Gély, Marie; Pittiglio, Claudia; Pinto, Julio; Chevalier, Véronique.
Afiliação
  • Tran A; CIRAD, UPR AGIRs, Ste-Clotilde, Reunion Island.
  • Trevennec C; CIRAD, UMR TETIS, Ste-Clotilde, Reunion Island.
  • Lutwama J; Food and Agriculture Organization of the United Nations, Rome, Italy.
  • Sserugga J; Uganda Virus Research Institute, Entebbe, Uganda.
  • Gély M; Uganda Ministry of Agriculture, Animal Industry and Fisheries, Entebbe, Uganda.
  • Pittiglio C; CIRAD, UPR AGIRs, Montpellier, France.
  • Pinto J; Food and Agriculture Organization of the United Nations, Rome, Italy.
  • Chevalier V; Food and Agriculture Organization of the United Nations, Rome, Italy.
PLoS Negl Trop Dis ; 10(9): e0004999, 2016 09.
Article em En | MEDLINE | ID: mdl-27631374
ABSTRACT
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.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Febre do Vale de Rift / Zoonoses / Surtos de Doenças / Sistemas de Informação Geográfica Idioma: En Ano de publicação: 2016 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Febre do Vale de Rift / Zoonoses / Surtos de Doenças / Sistemas de Informação Geográfica Idioma: En Ano de publicação: 2016 Tipo de documento: Article