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

被引:21
作者
Mosomtai, Gladys [1 ]
Evander, Magnus [2 ]
Sandstrom, Per [3 ]
Ahlm, Clas [4 ]
Sang, Rosemary [1 ]
Hassan, Osama Ahmed [2 ]
Affognon, Hippolyte [1 ]
Landmann, Tobias [1 ]
机构
[1] Int Ctr Insect Physiol & Ecol, POB 30772, Nairobi 00100, Kenya
[2] Umea Univ, Dept Clin Microbiol, Virol, Umea, Sweden
[3] Swedish Univ Agr Sci, Fac Forest Sci, Dept Forest Resource Management, S-90183 Umea, Sweden
[4] Umea Univ, Dept Clin Microbiol, Infect Dis, Umea, Sweden
关键词
Rift Valley fever; Evapotranspiration; Normalized difference vegetation index; Animal density; Disease mapping; TIME-SERIES; OUTBREAK; EPIDEMIOLOGY; PREDICTION; GEOGRAPHY; CLIMATE; MODEL; EAST;
D O I
10.1016/j.ijid.2016.03.013
中图分类号
R51 [传染病];
学科分类号
100401 ;
摘要
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).
引用
收藏
页码:49 / 55
页数:7
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