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Spatial, seasonal and climatic predictive models of Rift Valley fever disease across Africa

Redding, David W., Tiedt, Sonia, Lo Iacono, Giovanni, Bett, Bernard and Jones, Kate E. (2017) Spatial, seasonal and climatic predictive models of Rift Valley fever disease across Africa Philosophical Transactions of the Royal Society B: Biological Sciences, 372 (1725).

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Abstract

Understanding the emergence and subsequent spread of human infectious diseases is a critical global challenge, especially for high-impact zoonotic and vector-borne diseases. Global climate and land-use change are likely to alter host and vector distributions, but understanding the impact of these changes on the burden of infectious diseases is difficult. Here, we use a Bayesian spatial model to investigate environmental drivers of one of the most important diseases in Africa, Rift Valley fever (RVF). The model uses a hierarchical approach to determine how environmental drivers vary both spatially and seasonally, and incorporates the effects of key climatic oscillations, to produce a continental risk map of RVF in livestock (as a proxy for human RVF risk). We find RVF risk has a distinct seasonal spatial pattern influenced by climatic variation, with the majority of cases occurring in South Africa and Kenya in the first half of an El Niño year. Irrigation, rainfall and human population density were the main drivers of RVF cases, independent of seasonal, climatic or spatial variation. By accounting more subtly for the patterns in RVF data, we better determine the importance of underlying environmental drivers, and also make space- and time-sensitive predictions to better direct future surveillance resources.

Item Type: Article
Divisions : Faculty of Health and Medical Sciences > School of Veterinary Medicine
Authors :
NameEmailORCID
Redding, David W.UNSPECIFIEDUNSPECIFIED
Tiedt, SoniaUNSPECIFIEDUNSPECIFIED
Lo Iacono, Giovannig.loiacono@surrey.ac.ukUNSPECIFIED
Bett, BernardUNSPECIFIEDUNSPECIFIED
Jones, Kate E.UNSPECIFIEDUNSPECIFIED
Date : 18 July 2017
Identification Number : 10.1098/rstb.2016.0165
Copyright Disclaimer : © 2017 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.
Uncontrolled Keywords : Africa; Bayesian spatial model; Climatic oscillations; Integrated Laplace Approximations; Rift Valley fever; Risk map
Additional Information : This article is part of the themed issue ‘One Health for a changing world: zoonoses, ecosystems and human well-being’.
Depositing User : Clive Harris
Date Deposited : 03 Nov 2017 09:19
Last Modified : 03 Nov 2017 09:19
URI: http://epubs.surrey.ac.uk/id/eprint/844810

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