M
Michael J. Tildesley
Researcher at University of Warwick
Publications - 125
Citations - 3591
Michael J. Tildesley is an academic researcher from University of Warwick. The author has contributed to research in topics: Population & Medicine. The author has an hindex of 27, co-authored 104 publications receiving 2246 citations. Previous affiliations of Michael J. Tildesley include University of Nottingham & John E. Fogarty International Center.
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Journal ArticleDOI
Vaccination and non-pharmaceutical interventions for COVID-19: a mathematical modelling study.
TL;DR: In this paper, the authors used epidemiological data from the UK together with estimates of vaccine efficacy to predict the possible long-term dynamics of SARS-CoV-2 under the planned vaccine rollout.
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Optimal reactive vaccination strategies for a foot-and-mouth outbreak in the UK
Michael J. Tildesley,Nicholas J. Savill,Nicholas J. Savill,Darren J. Shaw,Rob Deardon,Stephen P. Brooks,Mark E. J. Woolhouse,Bryan T. Grenfell,Bryan T. Grenfell,Matthew James Keeling +9 more
TL;DR: A model of FMD spread is used to investigate the optimal deployment of reactive ring vaccination of cattle constrained by logistical resources, and the predicted optimal ring size is highly dependent upon logistical constraints but is more robust to epidemiological parameters.
Journal Article
Epidemic predictions in an imperfect world
TL;DR: This work uses a comprehensive database of the UK cattle trade network to determine the quantity of network data required to give accurate epidemiological predictions, and finds that by targeting nodes with the highest number of movements, accurate predictions on the size and spatial spread of epidemics can be made.
Journal Article
Inference for individual-level models of infectious diseases in large populations
Rob Deardon,Stephen P. Brooks,Bryan T. Grenfell,Matthew James Keeling,Michael J. Tildesley,Nicholas J. Savill,Darren J. Shaw,Mark E. J. Woolhouse +7 more
TL;DR: A methodology that can be used to estimate parameters for such large, and/or incomplete, data sets for the UK 2001 foot-and-mouth disease (FMD) epidemic is detailed.
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Modelling optimal vaccination strategy for SARS-CoV-2 in the UK.
TL;DR: In this paper, the optimal targeting of vaccination within the UK, with the aim of minimising future deaths or quality adjusted life year (QALY) losses, is investigated, and it is shown that targeting older age groups first is optimal and may be sufficient to stem the epidemic if the vaccine prevents transmission as well as disease.