Mike Gravenor is a professor of epidemiology within the medical school at Swansea University, and a member of the Welsh Government’s Technical Advisory Cell.
When the Welsh Government realised it needed locally-relevant modelling of Covid-19 developments, it contacted Gravenor to ask what was possible.
“Modelling has played a very prominent role in trying to understand the epidemic and to plan control policies. And these models are very, very detailed, including information for the whole of the UK. So we had access to that output but we wanted to run slightly different scenarios for Wales, and use some of the additional information we had for Wales.
“I’ve got a background in epidemiological modelling, but not models of this scale, and the timescale they were asking was pretty frightening! So I contacted Biagio Lucini, Swansea University’s PI for Supercomputing Wales, and asked for help,” Gravenor says.
Lucini opened a new project to investigate the possibility of running existing modelling software on the Supercomputing Wales cluster, and adapting them for Wales-specific scenarios.
Using Supercomputing Wales has been essential to the process, Gravenor says.
“We still have a lot of uncertainty about this disease and how it spreads. We understand the general processes, but to try to answer precise policy questions, such as what happens if you allow certain activities or open schools in certain way, the outcome depends on a huge amount of unknowns. If every time you run the model you have to run it for many, many thousands of parameter combinations, that can only be rationalised by some pretty powerful computing.”
Senior Research Software Engineer Mark Dawson took on much of the work in adapting the code to Supercomputing Wales.
“Historically, someone in Mike’s position would just have been given access to a supercomputer and the rest would be down to them. But researchers are experts in their specific domain: they can’t always be expected to also be experts in supercomputing. Having the support and expertise of Research Software Engineers is about providing computational expertise to researchers, so they’ve got the tools they need to explore new and exciting territory.” he says.
Dawson has developed the code to a level where researchers can run scenarios themselves and quickly answer questions from the Welsh government.
Feedback from Government has been positive, Gravenor says, due to the fast turnaround from Supercomputing Wales.
“To get the models running within days, then build in more and more Wales-specific data – they’ve been really happy with the progress we’ve shown.”
Update May 2021:
Dr Ben Thorpe, Dr Mark Dawson, and Dr Ed Bennett of the Supercomputing Wales Research Software Engineer team have continued to work closely with Prof. Biagio Lucini, Professor of Mathematics and Supercomputing Wales Swansea Principal Investigator, and Prof Mike Gravenor, Professor of Epidemiology and Biostatistics at the Swansea University Medical School, to support the Welsh Government’s efforts to model and understand the spread of COVID-19 in Wales. This has included developing and optimising an epidemiological model specific to the Welsh context, and applying that model to produce estimates of how the spread may change based on changes in policy and behaviour. Results of these predictions formed a significant part of the Reasonable Worst Case analysis published by the Welsh Government’s Technical Advisory Cell, and drove the decision making around the firebreak lockdown in October–November 2020 and the early move to tier four restrictions before Christmas 2020. This work takes advantage of the RSE team’s unique skillset to rapidly develop, modify, and deploy software to respond to the changing real-world situation, and also relies on the Supercomputing Wales High-Performance Computing infrastructure in Swansea to run the analysis at speed, allowing it to complete in time to inform ministerial decisions. The hardware resources and Research Software Engineering team provided by Supercomputing Wales were a key enabler for this activity; had these resources not been available, then this vital work would not have been possible.