A dynamic, climate-driven model of Rift Valley fever

  • Joseph Leedale | j.leedale@liverpool.ac.uk School of Environmental Sciences, University of Liverpool, Liverpool, United Kingdom.
  • Anne E. Jones Department of Epidemiology and Population Health, Institute of Infection and Global Health, University of Liverpool, Liverpool, United Kingdom.
  • Cyril Caminade Department of Epidemiology and Population Health, Institute of Infection and Global Health, University of Liverpool, Liverpool; National Institute for Health Research, Health Protection Research Unit in Emerging and Zoonotic Infections, Liverpool, United Kingdom.
  • Andrew P. Morse School of Environmental Sciences, University of Liverpool, Liverpool; National Institute for Health Research, Health Protection Research Unit in Emerging and Zoonotic Infections, Liverpool, United Kingdom.

Abstract

Outbreaks of Rift Valley fever (RVF) in eastern Africa have previously occurred following specific rainfall dynamics and flooding events that appear to support the emergence of large numbers of mosquito vectors. As such, transmission of the virus is considered to be sensitive to environmental conditions and therefore changes in climate can impact the spatiotemporal dynamics of epizootic vulnerability. Epidemiological information describing the methods and parameters of RVF transmission and its dependence on climatic factors are used to develop a new spatio-temporal mathematical model that simulates these dynamics and can predict the impact of changes in climate. The Liverpool RVF (LRVF) model is a new dynamic, process-based model driven by climate data that provides a predictive output of geographical changes in RVF outbreak susceptibility as a result of the climate and local livestock immunity. This description of the multi-disciplinary process of model development is accessible to mathematicians, epidemiological modellers and climate scientists, uniting dynamic mathematical modelling, empirical parameterisation and state-of-the-art climate information.

Downloads

Download data is not yet available.
Published
2016-03-31
Section
Original Articles
Keywords:
Rift Valley fever, Epidemiology, Climate, Mathematical modelling, Vector-borne diseases
Statistics
Abstract views: 2085

PDF: 688
Appendix: 236
HTML: 1528
Share it

PlumX Metrics

PlumX Metrics provide insights into the ways people interact with individual pieces of research output (articles, conference proceedings, book chapters, and many more) in the online environment. Examples include, when research is mentioned in the news or is tweeted about. Collectively known as PlumX Metrics, these metrics are divided into five categories to help make sense of the huge amounts of data involved and to enable analysis by comparing like with like.

How to Cite
Leedale, J., Jones, A., Caminade, C., & Morse, A. (2016). A dynamic, climate-driven model of Rift Valley fever. Geospatial Health, 11(1s). https://doi.org/10.4081/gh.2016.394

Most read articles by the same author(s)