I am a first-year Ph.D. student in the MathSys CDT and I am interested in applying mathematics to systems in the biological and social sciences. I am particularly interested in epidemiology, specifically, the effect of climate change on vector-borne disease spread. My research involves modelling the population size of mosquitoes as a function of the climate (temperature and rainfall are the main two driving factors) and using this population size to estimate epidemic metrics such as the basic reproduction number. I'm currently using climate change predictions generated by the Community Earth System ModelLink opens in a new window to examine spatial and temporal variation in these epidemic metrics globally from 1850 to 2100.
A.R. Kaye, W.S. Hart, J. Bromiley, S. Iwami, R.N. Thompson, A direct comparison of methods for assessing the threat from emerging infectious diseases in seasonally varying environments, Journal of Theoretical Biology (2022), doi: https://doi.org/10.1016/j.jtbi.2022.111195
MSc Individual project (2021) - Modelling the Impact of a Changing Environment on Vector-Borne Disease Epidemic Risks
- The probability that a large outbreak of Zika virus occurs given an initial infected case varies periodically throughout the year, with this change being driven by varying mosquito populations.
- Here I considered two metrics of epidemic risk - the instantaneous epidemic risk (IER) and the case epidemic risk (CER). The IER assumes that after the introduction of the first case, transmission conditions remain static but the CER allows for varying transmission conditions.
- A published temperature-dependent mosquito population model was built into a model that described the transmission of Zika virus and both the IER and CER were computed for various towns around the Trentino and Veneto regions of Northern Italy in order to examine the differences between the two metrics.
- Supervised by Dr Robin ThompsonLink opens in a new window and Dr Mike TildesleyLink opens in a new window.
MSc Research Study Group (2021) - Adaptive Management in an Ongoing Pandemic
- Adaptive management is the process of observing a system after intervention and examining the effectiveness of this intervention. This has mainly been applied to conservation problems but we sought to examine the effect of various lockdown strategies on the COVID-19 pandemic.
- Supervised by Dr Ben AtkinsLink opens in a new window and Dr Ed HillLink opens in a new window.
MMath Project (2019/20) - Modeling Evolutionary Biology using Multiplayer Game Theory
- I took a game-theoretic approach to model how species-specific traits give individuals an advantage when competing for resources.
- The project generalised the well studied "Hawks and Doves" game to an arbitrary number of players, along with introducing some interesting new strategies.
- Supervised by Dr Louise DysonLink opens in a new window.
URSS Summer Project (2019) - Controlling the Spread of Nipah Virus in Bangladesh
- Nipah virus is a neglected tropical disease with the majority of cases occurring in Bangladesh and India. It is a zoonotic disease and the majority of infections occur from drinking date palm sap which has been contaminated with infected bat urine.
- An SEIR model was used to describe the spread of the disease with vaccine classes added later. Parameter fitting was done using adaptive approximate Bayesian computation.
- The final part of the project focused on estimating the effect vaccine efficacy and distribution would have on the size of outbreaks.
- Supervised by Dr Mike TildesleyLink opens in a new window and Dr Louise DysonLink opens in a new window. This project built on work previously done by Emma SouthallLink opens in a new window in her MSc project.
MSc in Mathematics for Real-World Systems, University of Warwick (2020-2021) - Distinction
MMath in Mathematics, University of Warwick (2016-2020) - First Class Honours