Episode published: 03/08/20
In episode #23 Ciara Dangerfield is joined by Dr Robin Thompson to learn about about how data is being used to inform the mathematical models behind the models of COVID-19. Robin is a Junior Research Fellow in mathematical epidemiology at Christ Church, University of Oxford. Find out more about Robin’s work here: robin-thompson.co.uk or follow him on twitter @RobinNThompson. If you’re interested in the topics covered check, out Robin’s Oxford Mathematics public lecture on mathematical models of infectious disease outbreaks here: https://www.youtube.com/watch?v=m6Hr69JH_wA
00:00 – Episode description
00:50 – Introductions
02:00 – Types and uses of data within COVID-19 models
06:30 – Types of statistical method
09:05 – Issues with the current data
11:14 – How to cope with such deficiencies
15:55 – How to account for uncertainty
17:55 – Is widespread testing important for improving model predictions
22:40 – Explaining “RAMP”
25:30 – Wrap-up recommendations
28:45 – How can mathematicians help with current modelling challenges
31:45 – Contact details
Dr Robin Thompson helps explain how data is being used to inform the mathematical models behind the models of COVID-19
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