Karyn Morrissey

Turing Fellow Karyn Morrissey discusses her intriguing work developing a population model on COVID-19 exposure by looking at time use patterns alongside demographic and socioeconomic status

What are you working on currently?

Lots of different things – that’s the beauty of being a data scientist!  However, in my work with other Turing colleagues my main focus is developing a population model which looks at COVID-19 exposure across different areas based on individual time use patterns, such as how long people spend at work each day, how long they spend shopping etc, and demographic and socioeconomic status. As my research focuses on health inequalities in general, I’m particularly interested in the role deprivation can play in someone’s likelihood of being exposed to COVID-19 across different areas of the UK.

What's been the most surprising thing to come out of your research?

The amazing time use data, such as the UK Time Use Survey 2014/2015, that you can access in the UK and the fact that people spend so much of their time at home, even out of lockdown.

My take home message from this work is that we really need to start understanding our indoor environment better, for example indoor air quality in our homes, our behaviours around ventilation, the impact of humidity in the home on mould growth - the list is endless. We spend between 70 and 90 per cent of our time indoors, and yet most of our work on human health and the environment focuses on the outdoors. I am currently Principle Investigator on an European Regional Development Fund (ERDF) funded project called Smartline where we are starting to try and understand these issues through real-time environmental sensors in the home environment, so watch this space!

What has been the highlight of your Turing time?

Working with Turing colleagues in Leeds and other data scientists in Exeter (my base), UCL and Cambridge on the COVID-19 model. It was truly a melding of different data science areas – disease modelling, individual behavioural modelling, spatial modelling and some really large datasets. Also, getting to grips with how people spend their time over the course of a day – truly fascinating. 

What gets you up in the morning?

Trying to understand how far data science can be used to understand real-life human behaviour – not just trying to represent a population by a few characteristics such as age and sex or gender, but truly representing people’s diverse behaviours.

If you could choose anyone in the world as a mentor, who would you pick?

Probably Mary Robinson – she was elected first Irish female president when I was a child and through her presidency and work with the UN, she has always inspired me as a woman in a man’s workplace.

Who would you invite to your dream dinner party?

It’s a long list but:

  • Mary Robinson
  • Anthony Hopkins 
  • Professor Michael Marmot
  • David Mitchell (the author)
  • Haruki Murakami 
  • Kathryn Budig (a yoga teacher)
  • My dog Alfie

And finally, when not working what can you be found doing?

Walking my dog Alfie, reading, doing yoga, and pre-lockdown - swimming.