I am an early career researcher interested in collaborative modelling efforts to support policy in epidemic outbreaks. My background is in epidemiology, geography, and research funding, and I have a strong interest in collaborative and interdisciplinary approaches to public health.
Affiliations
Department of Infectious Disease Epidemiology and Dynamics
Faculty of Epidemiology and Population Health
Teaching
At LSHTM I have previously contributed teaching to the MSc Epidemiology.
Research
I am broadly interested in the role of infectious disease modelling in decision making during epidemic outbreaks. Specifically, I am interested in the emergent properties of modelling collaborations, both quantitatively (e.g. better predictive power of multi-model ensembles) and qualitatively (e.g. creating a scientific consensus for policy).
Over the last year I have developed and lead two cross-European collaborations for COVID-19 forecast and scenario modelling, working directly with the European Centre for Disease Prevention and Control and colleagues across Europe and the US. Previously, I worked on the UK COVID-19 response contributing to estimating the effective reproduction number, forecasting, and data management. Prior to the COVID-19 emergency response, I worked on modelling dengue fever in the Philippines, leading to a successful MPhil upgrading.
Over the last year I have developed and lead two cross-European collaborations for COVID-19 forecast and scenario modelling, working directly with the European Centre for Disease Prevention and Control and colleagues across Europe and the US. Previously, I worked on the UK COVID-19 response contributing to estimating the effective reproduction number, forecasting, and data management. Prior to the COVID-19 emergency response, I worked on modelling dengue fever in the Philippines, leading to a successful MPhil upgrading.
Research Area
Modelling
Surveillance
Epidemiology
Mathematical Modelling
Disease and Health Conditions
Infectious diseases
Selected Publications
Exploring surveillance data biases when estimating the reproduction number: with insights into subpopulation transmission of COVID-19 in England.
2021
Philosophical transactions of the Royal Society of London. Series B, Biological sciences
The impact of population-wide rapid antigen testing on SARS-CoV-2 prevalence in Slovakia.
2021
Science (New York, N.Y.)
Estimating the time-varying reproduction number of SARS-CoV-2 using national and subnational case counts
2020
Wellcome Open Research
Short-term forecasts to inform the response to the Covid-19 epidemic in the UK
2020
medRxiv preprint - BMJ Yale