ArticlePLoS neglected tropical diseases2016
Development and Assessment of a Geographic Knowledge-Based Model for Mapping Suitable Areas for Rift Valley Fever Transmission in Eastern Africa.
Article in PLoS neglected tropical diseases, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
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Who cites it
30 citing papers in PubMed.
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- Mapping heartwater risk in Guadeloupe using a combination of spatial modelling approaches.Scientific reports · 2025Article
- Editorial: One Health approaches and modeling in parasitology in the climate change framework and possible supporting tools adopting GIS and remote sensing.Frontiers in parasitology · 2025Article
- Risk Mapping of African Swine Fever in Domestic Pigs and Wild Boars to Enhance Management and Surveillance in Asia.Transboundary and emerging diseases · 2025Article
- Development and application of a WebGIS-based prediction system for multi-criteria decision analysis of porcine pasteurellosis.Scientific reports · 2024Article
- Modelling the risk of Japanese encephalitis virus in Victoria, Australia, using an expert-systems approach.BMC infectious diseases · 2024Article
- Article
- Entomological survey of the potential vectors of Rift Valley fever virus and absence of detection of the virus genome from the vectors in various niches in the southern half of the Great Rift Valley of Ethiopia.Veterinary medicine and science · 2022Article
- No evidence of Rift Valley fever antibodies in veterinarians and sheep in Northern Palestine.Veterinary world · 2022Article
- Application of Spatial Risk Assessment Integrated With a Mobile App in Fighting Against the Introduction of African Swine Fever in Pig Farms in Thailand: Development Study.JMIR formative research · 2022Article
- Seroprevalence and Risk Factors of Crimean-Congo Hemorrhagic Fever in Cattle of Smallholder Farmers in Central Malawi.Pathogens (Basel, Switzerland) · 2021Article
- Assessment of foot-and-mouth disease risk areas in mainland China based spatial multi-criteria decision analysis.BMC veterinary research · 2021Article
- Risk factors for Rift Valley fever virus seropositivity in one-humped camels (One health (Amsterdam, Netherlands) · 2021Article
- Scoping future outbreaks: a scoping review on the outbreak prediction of the WHO Blueprint list of priority diseases.BMJ global health · 2021Article
- Article
- Mapping of Ebola virus spillover: Suitability and seasonal variability at the landscape scale.PLoS neglected tropical diseases · 2021Article
- Sero-prevalence of West Nile virus and Rift Valley fever virus infections among cattle under extensive production system in South Omo area, southern Ethiopia.Tropical animal health and production · 2021Article
- Sero-prevalence of brucellosis, Q-fever and Rift Valley fever in humans and livestock in Somali Region, Ethiopia.PLoS neglected tropical diseases · 2021Article
- Article
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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