Statistics Seminar - Statistical inference for emerging diseases inspired by Covid-19
| Dates: | 11 December 2024 |
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| Times: | 14:00 - 14:45 |
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| What is it: | Seminar |
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| Organiser: | Department of Mathematics |
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| Who is it for: | University staff, External researchers, Current University students |
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| Speaker: | Prof. Peter Neal |
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Abstract
(joint work with Prof Frank Ball)
The Covid-19 pandemic has transformed the landscape in terms of how mathematical modelling of infectious diseases is viewed both in the academic community and wider population and has provided a stimulus for much research. I will talk about one research direction, motivated by Covid-19.
We start from the question:
What does the (partial) observation of the times, at which individuals show symptoms to a disease, tell us about the number of individuals infected in a population?
For a general stochastic epidemic (SIR) model we are able to answer this question. By using a birth-death process approximation we can obtain explicit distributions for the number of people infectious when the infection and recovery rates and probability of detection of cases all vary over time. The key consequence of this, from a statistical perspective, is that it yields a likelihood for the observation process of detection times of cases without having to impute infection times. This enables us to:
Provide fresh insight into the likelihood of ongoing epidemics with the results supporting a Bayesian approach to analysing such epidemic models.
Through a fast approximation of the likelihood analyse European Covid-19 data and evaluate the effectiveness of control measures.
Speaker
Prof. Peter Neal
Organisation: Univ. of Nottingham
Travel and Contact Information
Find event
Frank Adams 2
Alan Turing Building
Manchester
