I am a PhD Candidate within the Department for Infectious Disease Epidemiology. My research is focused on using mathematical modelling techniques to understand how anti-malarial resistance spreads. I specifically look at malaria prevention interventions in young children and potential strategies to increase the effective life-span of these measures.
I spent most of 2020 working as part of the Imperial College COVID-19 Response Team. In the early stage of the pandemic, I was responsible for collating all information on cases outside of mainline China. This data was used to understand what the symptoms of COVID-19 were, along with the earliest estimates of the case fatality ratio. I also participated in a number of research studies estimating the reproduction number, most notably in Vo' in Italy and also in South Korea.
In 2020 I was awarded the Imperial College award for best graduate teaching assistant. Within the School of Public Health, I assist in delivering postgraduate modules as part of the Public Health, Epidemiology and Health Data Analytics masters programs. I teach courses about mathematical epidemiology, modelling of infectious diseases and mathematics for public health.
et al., 2021, Leveraging community mortality indicators to infer COVID-19 mortality and transmission dynamics in Damascus, Syria, Nature Communications, Vol:12, ISSN:2041-1723, Pages:1-10
et al., 2020, SARS-CoV-2 infection prevalence on repatriation flights from Wuhan City, China, Journal of Travel Medicine, Vol:27, ISSN:1195-1982, Pages:1-3
et al., 2020, Response to COVID-19 in South Korea and implications for lifting stringent interventions, BMC Medicine, Vol:18, ISSN:1741-7015, Pages:1-12
et al., 2020, Potential impact of the COVID-19 pandemic on HIV, TB and malaria in low- and middle-income countries: a modelling study, The Lancet Global Health, Vol:8, ISSN:2214-109X, Pages:e1132-e1141
et al., 2020, Suppression of a SARS-CoV-2 outbreak in the Italian municipality of Vo', Nature, Vol:584, ISSN:0028-0836, Pages:425-429
et al., 2020, Estimates of the severity of coronavirus disease 2019: a model-based analysis., Lancet Infectious Diseases, Vol:20, ISSN:1473-3099, Pages:669-677
et al., 2020, Report 37: Children’s role in the COVID-19 pandemic: a systematic review of early surveillance data on susceptibility, severity, and transmissibility
et al., 2020, Report 9: Impact of non-pharmaceutical interventions (NPIs) to reduce COVID19 mortality and healthcare demand
et al., 2020, Report 4: Severity of 2019-novel coronavirus (nCoV)