Theo Kypraios -- Bayesian nonparametric inference for stochastic infectious disease models [IN PERSON]
|Dates:||27 February 2023|
|Times:||14:00 - 15:00|
|What is it:||Seminar|
|Organiser:||Department of Mathematics|
|Who is it for:||University staff, External researchers, Current University students|
Join us for this seminar by Theo Kypraios (University of Nottingham) as part of the North West Seminar Series in Mathematical Biology and Data Sciences. Details of the full series can be found here https://www.cms.livjm.ac.uk/APMSeminar/
The talk will be hosted in person in the Simon Building, Room 4.38. For those who cannot attend in person the talk will also be streamed via zoom, please contact firstname.lastname@example.org or email@example.com for the zoom link, or sign up to the mailing list.
Title: Bayesian nonparametric inference for stochastic infectious disease models
Abstract: Infectious disease transmission models require assumptions about how the pathogen spreads between individuals. These assumptions may be somewhat arbitrary, particularly when it comes to describing how transmission varies between individuals of different types or in different locations and may in turn lead to incorrect conclusions or policy decisions.
In this talk, we will present a novel and general Bayesian nonparametric framework for transmission modelling which removes the need to make such specific assumptions with regards to the infection process. We use multi-output Gaussian process prior distributions to model different infection rates in populations containing multiple types of individuals. Further challenges arise because the transmission process itself is unobserved, and large outbreaks can be computationally demanding to analyse. We address these issues by data augmentation and a suitable efficient approximation method. Simulation studies using synthetic data demonstrate that our framework gives accurate results. Finally, we use our methods to enhance our understanding of the transmission mechanisms of the 2001 UK Foot and Mouth Disease outbreak.
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Organisation: University of Nottingham
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