Episode 6: How do we predict the spread of COVID-19?

From the outset of COVID-19 being declared a public health emergency, the UK Government has been at great pains to stress its response has been guided by science.

Mathematical modelling has underpinned much of the advice given to Ministers to help them chart a way through the crisis. But how does mathematical modelling work? How accurate is it? And what role will modelling continue to play in the coming months as lockdowns around the world continue to ease?

To help answer these questions, I was joined for this episode by Dr Ellen Brooks Pollock, Senior Lecturer in Infectious Disease Mathematical Modelling.

In addition to her work at the Bristol Veterinary School and the Bristol Health Protection Research Unit, Ellen is a member of the Scientific Pandemic Infleunza Group on Modelling that informs the SAGE committee of scientists, and the SAGE-subgroup on children and schools that advises the government.

During the conversation, Ellen talks me through the ‘R’ number (or ‘reproduction’ number), the serial interval and how both of these metrics are used to predict COVID-19 transmission in the community. We also discuss how modellers factor in a whole range of unknown variables, such as the number of asymptomatic spreaders of COVID-19, when making their predictions. Finally, we discuss Ellen’s new research project to explore and predict virus transmission in a University setting.

My thanks to Ellen for sharing her expertise on this important issue.

 

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