Publication Type

Journal Article

Journal Name

International Journal of Infectious Diseases

Publication Date

5-1-2016

Abstract

Objective: Rift Valley fever (RVF) is a mosquito-borne infection with great impact on animal and human health. The objectives of this study were to identify ecological factors that explain the risk of RVF outbreaks in eastern and central Kenya and to produce a spatially explicit risk map. Methods: The sensitivity of seven selected ecological variables to RVF occurrence was assessed by generalized linear modelling (GLM). Vegetation seasonality variables (from normalized difference vegetation index (NDVI) data) and 'evapotranspiration' (ET) (metrics) were obtained from 0.25-1 km MODIS satellite data observations; 'livestock density' (N/km2), 'elevation' (m), and 'soil ratio' (fraction of all significant soil types within a certain county as a function of the total area of that county) were used as covariates. Results: 'Livestock density', 'small vegetation integral', and the second principal component of ET were the most significant determinants of RVF occurrence in Kenya (all p ≤ 0.01), with high RVF risk areas identified in the counties of Tana River, Garissa, Isiolo, and Lamu. Conclusions: Wet soil fluxes measured with ET and vegetation seasonality variables could be used to map RVF risk zones on a sub-regional scale. Future outbreaks could be better managed if relevant RVF variables are integrated into early warning systems.

Keywords

Animal density, Disease mapping, Evapotranspiration, Normalized difference vegetation index, Rift Valley fever

PubMed ID

26996461

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