Evolution, behaviour and environment

photo of Rosanna Barnard

Dr Rosanna Barnard

Post:Research Associate (Evolution, Behaviour and Environment)
Location:JMS BUILDING 5B23
Personal homepage:home
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I am a mathematician by training and my research to date has involved using mathematical models and computational techniques to provide insight into real world processes, in particular in biological fields such as neuroscience and epidemiology. I am also passionate about research communication and widening participation in science and research.
During my undergraduate, a 4-year integrated masters course in Mathematics, I researched the dynamics of variant interaction in a model of antigenic variation, a process where a pathogen varies the antigens or surface markers present on the surface of an infected cell with the aim of delaying the immune system's response to infection. 
Following my undergraduate I accepted a 3.5-year EPSRC-funded PhD studentship, under the supervision of Professor Istvan Kiss and Dr Luc Berthouze, looking at modelling and analysing processes occurring on complex networks. During this time I studied a model describing the activity-dependent growth and development of a network of neurons, investigating the effects of different spatial arrangements of neurons on the resulting electrical dynamics of the `brain'. I also researched the dynamics of susceptible-infected-recovered (SIR) type diseases spreading through networks of individuals, firstly deriving and validating a series of model equations describing the disease spreading across a complex network, and then improving an analytical approximation for the epidemic threshold in a pairwise SIR model.
Towards the end of my doctorate, I obtained a position as a Research Fellow in Infectious Disease Modelling working with Dr Pierre Nouvellet in the Evolution, Behaviour & Environment research group in the School of Life Sciences. My current research involves using mathematical and computational techniques to predict the spatial or geographic spread of infectious disease, in particular using region-specific incidence data from the 2013-16 West African Ebola epidemic.