I am a 3rd year DPhil student in the Department of Statistics supervised by Professor Christl Donnelly and funded by the National Institute for Health and Care Research (NIHR) Health Protection Research Unit in Emerging and Zoonotic Infections (HPRU-EZI). My thesis is entitled “Epidemiological modelling and analysis of COVID-19, MERS and other high-consequence infectious disease transmission risks”. Broadly speaking, my research focusses on the use of statistical and mathematical modelling techniques for the analysis of outbreaks of infectious diseases, with a focus on COVID-19. I have a strong interest in the use of modelling in informing public health policy: in January - April 2022, I worked at the UK Health Security Agency (UKHSA) analysing the impact of changing COVID-19 case definitions and testing policies on estimates of the effective reproduction number, and throughout June – September 2022 I worked as a statistician for the Infected Blood Inquiry.
I have an undergraduate degree in Mathematics, Operational Research, Statistics and Economics with Intercalated Year from the University of Warwick (2017) and a Masters in Statistics from Imperial College London (2018). I am a Visiting Researcher at the MRC Centre for Global Infectious Disease Analysis at Imperial College London where I worked from 2019 – 2020 before beginning my DPhil.
Inferring community transmission of SARS-CoV-2 in the United Kingdom using the ONS COVID-19 Infection Survey
McCabe R. et al, (2024), Infectious Disease Modelling, 9, 299 - 313
Public awareness of and opinions on the use of mathematical transmission modelling to inform public health policy in the United Kingdom.
McCabe R. and Donnelly CA., (2023), J R Soc Interface, 20
Public awareness of and opinions on the use of mathematical transmission modelling to inform public health policy in the United Kingdom
McCabe R. and Donnelly CA., (2023)
Marburg Virus Disease outbreaks, mathematical models, and disease parameters: a Systematic Review
Cuomo-Dannenburg G. et al, (2023)
Alternative epidemic indicators for COVID-19: a model-based assessment of COVID-19 mortality ascertainment in three settings with incomplete death registration systems
McCabe R. et al, (2023)