nimue is an extension to the squire package that allows vaccination to be included. For detailed information on the base model structure and parameterisation please visit the squire webpage. The model has been used for vaccine delivery optimisation1 and as part of model trajectories in support of the WHO Essential Supplies Forecasting Tool.
nimue has also been used for the first estimates of the global impact of the COVID-19 vaccinations, showing almost 20 million deaths were averted due to vaccination during the first of vaccinations2.
A. B. Hogan, P. Winskill, O. J. Watson, P. G. T. Walker, C. Whittaker, M. Baguelin, N. F. Brazeau, G. D. Charles, K. A. M. Gaythorpe, A. Hamlet, E. Knock, D. J. Laydon, J. A. Lees, A. Løchen, R. Verity, L. K. Whittles, F. Muhib, K. Hauck, N. M. Ferguson, A. C. Ghani, Within-country age-based prioritisation, global allocation, and public health impact of a vaccine against SARS-CoV-2: A mathematical modelling analysis. Vaccine. 39, 2995–3006 (2021). (https://www.sciencedirect.com/science/article/pii/S0264410X21004278?via%3Dihub) ↩︎
O. J. Watson, G. Barnsley, J. Toor, A. B. Hogan, P. Winskill, A. C. Ghani, Global impact of the first year of COVID-19 vaccination: a mathematical modelling study. Lancet Infect. Dis. (2022). (https://www.thelancet.com/journals/laninf/article/PIIS1473-3099(22)00320-6/fulltext). ↩︎
OJ Watson
Associate Professor
I’m an Associate Professor at Imperial College London, supported by an Eric and Wendy Schmidt AI in Science Fellowship. I’m based within Imperial’s AI Initiative, I-X, and the MRC Centre for Global Infectious Disease Analysis.
I develop open, reproducible methods at the intersection of infectious disease modelling, mortality estimation, and AI for public health — supporting decision-making and improving data equity. Recent applications include malaria and COVID-19.
Previously, I was a Schmidt Science Fellow at the London School of Hygiene and Tropical Medicine, and held postdoctoral positions at Brown University and Imperial College London.