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Global mosquito-borne virus control using Wolbachia in current and future climates: a computational modelling approach

Infectious & Tropical Diseases

London United Kingdom Climate Science Computational Mathematics Data Analysis Data Science Ecology Entomology Environmental Biology Epidemiology Machine Learning Mathematical Modelling

About the Project

One of the most promising technologies for controlling human viruses spread by mosquitoes (e.g. dengue, chikungunya, Zika) involves the infection of mosquitoes with Wolbachia, a naturally occurring endosymbiotic bacterium that reduces virus transmission. The first epidemiological evidence to support this novel approach was published in September 2020, and trials are underway in a further dozen countries worldwide.

Different Wolbachia strains have different sensitivities to temperature. This quantitative project will develop mathematical models to inform which strains are anticipated to work best for different regions of the world. It will also develop projections for informing optimal strains for different regions of the world in the future under different climate change scenarios.

The student will not only gain valuable experience in cutting-edge modelling methods but, by working closely with the World Mosquito Program, will also have the opportunity to engage with all aspects of this technology – from theory to public health intervention applications.


The student will need TO HAVE ALREADY excellent quantitative and computational skills e.g. a significant component of mathematical and/or computational modelling in their previous degree(s). They will need to be proficient in a common-use programming language e.g. R, Python and have an interest in infectious disease epidemiology.

Funding Notes

This will be funded through MRC LID: View Website
Funding is secured by the student and supervisor through jointly developing an application to the MRC

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