Research output per year
Research output per year
Personal profile
Research interests
Bayesian modelling methodology for pandemic preparedness
Education/Academic qualification
PhD, Using Computationally Intensive Bayesian methods to model movement and survival of juvenile Atlantic salmon salmo salar L. in a Northern Scottish river, University of Cambridge
Award Date: 23 Oct 2010
External positions
Senior Research Associate, MRC Biostatistics Unit, University of Cambridge
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Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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Combining models to generate a consensus effective reproduction number R for the COVID-19 epidemic status in England
Nowcasts Model Contributing Group, 14 Mar 2024, In: Epidemiology and Infection. 152, e59.Research output: Contribution to journal › Article › peer-review
Open Access -
Combining models to generate consensus medium-Term projections of hospital admissions, occupancy and deaths relating to COVID-19 in England
Manley, H., Bayley, T., Danelian, G., Burton, L., Finnie, T., Charlett, A., Watkins, N. A., Birrell, P., De Angelis, D., Keeling, M., Funk, S., Medley, G., Pellis, L., Baguelin, M., Ackland, G. J., Hutchinson, J., Riley, S. & Panovska-Griffiths, J., 22 May 2024, In: Royal Society Open Science. 11, 5, 231832.Research output: Contribution to journal › Article › peer-review
Open Access -
Improving the representativeness of UK’s national COVID-19 Infection Survey through spatio-temporal regression and post-stratification
the COVID−19 Infection Survey Tea, Dec 2024, In: Nature Communications. 15, 1, 5340.Research output: Contribution to journal › Article › peer-review
Open Access -
Risk of SARS-CoV-2 reinfection during multiple Omicron variant waves in the UK general population
Wei, J., Stoesser, N., Matthews, P. C., Khera, T., Gethings, O., Diamond, I., Studley, R., Taylor, N., Peto, T. E. A., Walker, A. S., Pouwels, K. B., Eyre, D. W., Rourke, E., Thomas, T., Pienaar, D., Preece, J., Crofts, S., Lloyd, L., Bowen, M. & Ayoubkhani, D. & 53 others, , Dec 2024, In: Nature Communications. 15, 1Research output: Contribution to journal › Article › peer-review
Open Access -
Sample-efficient neural likelihood-free Bayesian inference of implicit HMMs
Ghosh, S., Birrell, P. J. & De Angelis, D., 2024, In: Proceedings of Machine Learning Research. 238, p. 4888-4896 9 p.Research output: Contribution to journal › Conference article › peer-review