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Predictive Models of Meningitis Risk in the African Meningitis Belt

2014-16 Seed Grant

The complex ecological factors driving the distinct seasonality of meningococcal disease epidemics in the African meningitis belt are poorly understood. Evidence suggests that dust, low absolute humidity, rainfall, wind direction and velocity, land cover, and surface temperature may contribute, and a plausible biological mechanism by which these factors could increase risk of meningococcal disease among asymptomatic carriers has been proposed. We aim to develop, test, and validate an epidemiologic meningococcal disease risk model for Mali and Niger using climatic factors drawn from several high-resolution climate models including a recently published model of global dust circulation.

Our goal is to develop tools to better understand the role of environmental factors in predicting meningitis outbreaks in Africa. Developing these tools will set the stage for more extensive research aimed at modeling epidemiologic risk across the entire meningitis belt and identifying high-priority areas that would most benefit from vaccination, thus addressing a significant public health challenge.  

Collaborating institutions


Principal Investigators

Nicole E. Basta

Nicole E. Basta, Associate Research Scholar, Ecology and Evolutionary Biology

Elena Shevliakova

Elena Shevliakova, Senior Climate Modeler, Ecology and Evolutionary Biology

Paul Ginoux

Paul Ginoux, Visiting Research Collaborator, Atmospheric and Oceanic Sciences

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