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.
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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) ↩︎
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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
Imperial College Research Fellow
I am an Imperial College Research Fellow supported by an Eric and Wendy Schmidt AI in Science Fellowship, working within Imperial's new AI Initiative: I-X. My primary focus is as an infectious disease modeller, data scientist, epidemiologist and an R developer. My academic work has focussed on modelling the spread of malaria and COVID-19, based at Imperial College London, Brown University and the London School of Hygiene and Tropical Medicine.