Association of ecological factors with Rift Valley fever occurrence and mapping of risk zones in Kenya

作者：Mosomtai Gladys; Evander Magnus; Sandstrom Per; Ahlm Clas; Sang Rosemary; Hassan Osama Ahmed; Affognon Hippolyte; Landmann Tobias^*

来源：International Journal of Infectious Diseases, 2016, 46: 49-55.

DOI：10.1016/j.ijid.2016.03.013

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

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/km(2)), '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. (C) 2016 The Authors. Published by Elsevier Ltd on behalf of International Society for Infectious Diseases. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-ra1/4.01).

• 出版日期2016-5