Zobrazeno 1 - 10
of 112
pro vyhledávání: '"Birrell, Paul J."'
Autor:
Birrell, Paul J, Blake, Joshua, Kandiah, Joel, Alexopoulos, Angelos, van Leeuwen, Edwin, Pouwels, Koen, Ghosh, Sanmitra, Starr, Colin, Walker, Ann Sarah, House, Thomas A, Gay, Nigel, Finnie, Thomas, Gent, Nick, Charlett, André, De Angelis, Daniela
A central pillar of the UK's response to the SARS-CoV-2 pandemic was the provision of up-to-the moment nowcasts and short term projections to monitor current trends in transmission and associated healthcare burden. Here we present a detailed deconstr
Externí odkaz:
http://arxiv.org/abs/2408.04178
Likelihood-free inference methods based on neural conditional density estimation were shown to drastically reduce the simulation burden in comparison to classical methods such as ABC. When applied in the context of any latent variable model, such as
Externí odkaz:
http://arxiv.org/abs/2405.01737
Autor:
Corbella, Alice, McKinley, Trevelyan J., Birrell, Paul J., De Angelis, Daniela, Presanis, Anne M., Roberts, Gareth O., Spencer, Simon E. F.
Particle filtering methods can be applied to estimation problems in discrete spaces on bounded domains, to sample from and marginalise over unknown hidden states. As in continuous settings, problems such as particle degradation can arise: proposed pa
Externí odkaz:
http://arxiv.org/abs/2212.04400
Modelling the transmission dynamics of an infectious disease is a complex task. Not only it is difficult to accurately model the inherent non-stationarity and heterogeneity of transmission, but it is nearly impossible to describe, mechanistically, ch
Externí odkaz:
http://arxiv.org/abs/2208.14363
Health-policy planning requires evidence on the burden that epidemics place on healthcare systems. Multiple, often dependent, datasets provide a noisy and fragmented signal from the unobserved epidemic process including transmission and severity dyna
Externí odkaz:
http://arxiv.org/abs/2204.08901
Autor:
Brizzi, Francesco, Birrell, Paul J, Kirwan, Peter, Ogaz, Dana, Brown, Alison E, Delpech, Valerie C, Gill, O Noel, De Angelis, Daniela
Background: After a decade of a treatment as prevention (TasP) strategy based on progressive HIV testing scale-up and earlier treatment, a reduction in the estimated number of new infections in men-who-have-sex-with-men (MSM) in England had yet to be
Externí odkaz:
http://arxiv.org/abs/2010.00740
In recent years the role of epidemic models in informing public health policies has progressively grown. Models have become increasingly realistic and more complex, requiring the use of multiple data sources to estimate all quantities of interest. Th
Externí odkaz:
http://arxiv.org/abs/1706.02624
Autor:
Corbella, Alice, Zhang, Xu-Sheng, Birrell, Paul J., Boddington, Nicky, Presanis, Anne M., Pebody, Richard G., De Angelis, Daniela
Influenza remains a significant burden on health systems. Effective responses rely on the timely understanding of the magnitude and the evolution of an outbreak. For monitoring purposes, data on severe cases of influenza in England are reported weekl
Externí odkaz:
http://arxiv.org/abs/1706.02527
Autor:
Birrell, Paul J1,2 (AUTHOR) paul.birrell@ukhsa.gov.uk, Alexopoulos, Angelos2 (AUTHOR), De Angelis, Daniela1,2 (AUTHOR)
Publikováno v:
Journal of the Royal Statistical Society: Series A (Statistics in Society). Oct2023, Vol. 186 Issue 4, p640-641. 58p.
Autor:
Birrell, Paul J., Wernisch, Lorenz, Tom, Brian D. M., Held, Leonhard, Roberts, Gareth O., Pebody, Richard G., De Angelis, Daniela
Publikováno v:
The Annals of Applied Statistics, 2020 Mar 01. 14(1), 74-93.
Externí odkaz:
https://www.jstor.org/stable/26922885