Summary
I am Proleptic Lecturer and Imperial College Research Fellow supported by an Eric and Wendy Schmidt AI in Science Fellowship. I am part of the MRC Centre for Global Infectious Disease Analysis within the Department of Infectious Disease Epidemiology and currently sit in Imperial's new AI Initiative, I-X.
My research involves using mathematical models to better understand the spread of infectious diseases and estimate mortality in settings without robust vital registration services. I work primarily in three areas.
1. Malaria drug and diagnostic resistance modelling
2. Pandemic preparedness and vaccine impact modelling
3. Mortality estimation in humanitarian settings
For more information please see https://www.ojwatson.co.uk/
Background
My undergraduate degree was in Natural Sciences at Pembroke College, Cambridge before completing a master's degree in Systems Biology, working on multi-omic computational methods for identifying new biochemical reactions indicative of disease.
For my PhD I worked on integrating genetic information into malaria transmission modelling with Prof Azra Ghani, Dr Lucy Okell and Dr Robert Verity. This work was focussed on extending malaria transmission models that have been used in creating global technical strategies for malaria control by including parasite genetic information to answer policy questions related to pfhrp2/3 deletions and antimalarial resistance.
After my PhD, I spent time as a postdoc at Brown University in the Bailey Lab working on malaria population genetics and in the Department of Infectious Disease Epidemiology at Imperial, working with Dr Patrick Walker on modelling the transmission of COVID-19 in Low- and Middle-Income Countries and the impact of COVID-19 vaccination.
In 2021, I started a Schmidt Science Fellowship at the London School of Hygiene and Tropical Medicine working with Prof Francesco Checchi on mortality estimation in humanitarian settings, before returning to Imperial as an Eric and Wendy Schmidt AI Fellow.
Publications
Journals
Sheppard RJ, Watson OJ, Pieciak R, et al., 2024, Author Correction: Using mortuary and burial data to place COVID-19 in Lusaka, Zambia within a global context., Nat Commun, Vol:15
Meier-Scherling CPG, Watson OJ, Asua V, et al., 2024, Selection of artemisinin partial resistance Kelch13 mutations in Uganda in 2016-22 was at a rate comparable to that seen previously in South-East Asia., Medrxiv
Hogan AB, Wu SL, Toor J, et al., 2023, Long-term vaccination strategies to mitigate the impact of SARS-CoV-2 transmission: A modelling study., Plos Med, Vol:20
Bhatia S, Imai N, Watson OJ, et al., 2023, Lessons from COVID-19 for re-scalable data collection, Lancet Infectious Diseases, Vol:23, ISSN:1473-3099, Pages:E383-E388
Hogan A, Doohan P, Wu S, et al., 2023, Estimating long-term vaccine effectiveness against SARS-CoV-2 variants: a model-based approach, Nature Communications, Vol:14, ISSN:2041-1723, Pages:1-10