PhD Research Project: Modelling Climate Sensitive Infections in Arctic Populations

Many important infectious diseases are ‘climate sensitive’, as both the ecology of the host population and the epidemiology of the disease are critically dependent on climatic variables. Given rapid climate change, it is crucial that we understand how the spread of climate sensitive infections in wildlife populations may be impacted. This is especially relevant for Arctic societies, where households dependent on animal husbandry are particularly exposed and sensitive to changes due to climate change in the epidemiology of wildlife and farmed populations.

In this PhD you will develop mathematical models to understand the dynamics of climate sensitive infections. You build and analyse mechanistic models that represent infection dynamics using real-world data, with a particular focus on the impact of climatic variation. You will also assess the effectiveness of ‘climate envelope models’ for predicting the impact of climate change in these systems compared to fully dynamic models.

We are looking for a student with a background in applied mathematics (or related discipline) who is enthusiastic about applying mathematical skills to tackle a real-world biological problem. The project will be co-supervised by Dr Alex Best (Mathematics & Statistics), who will lead the mathematical modelling, and Dr Dylan Childs (Animal & Plant Sciences), who will lead the data analysis, and you will spend time in both departments. You will also interact with a diverse range of collaborators from an existing international network (CLINF) to obtain the data and develop the models.

How to Apply: How to apply: Go to http://www.sheffield.ac.uk/postgraduate/research/apply/applying after reading the information contained on that page click the link to the Postgraduate online application form

Funding Notes

This project will be funded by the Leverhulme Trust Centre for Advanced Biological Modelling