Computer modelling to determine Covid-19 airborne droplets risk
Computer modelling techniques and fluid mechanics are to be used together to understand the risk of the spread of Covid-19 airborne droplets in indoor spaces.
Engineers at the University of Glasgow are to lead a £1.35m research programme which brings together experts in fluid mechanics, modelling and computation from a total of five UK universities.
Over the course of the next 18 months, the researchers will develop a user-friendly online tool capable of predicting the spread of airborne droplets of fluid across spaces like shops, restaurants and schools. They hope that the tool will help users make more informed decisions about health and safety, supported by advice tailored to their unique spaces.
Airborne droplets can contain particles of the COVID-19 virus, produced when people carrying the infection breathe, cough, sneeze or speak. Current research suggests that people sharing space with virus-carrying droplets could be infected when they breathe them in, or touch their face after coming into contact with surfaces where the droplets have settled.
The researchers will work to unify existing computer and mathematical models of how droplets are carried on the air across indoor spaces of all sizes. They will also conduct their own research at wind tunnel testing facilities in Glasgow and Cambridge to create new fluid-dynamic models in a wide range of conditions.
The end result of their efforts will be called the Risk EvaLuatIon fAst iNtelligent Tool, or RELIANT. The system, set to run on mobile devices and computers, will allow users to custom-build detailed models of any indoor space and visualise how changes in seating arrangements, number of occupants and amount of ventilation affect the transport of droplets around the area. RELIANT will also be able to model the impact of face-masks on the spread of droplets.
The challenging computation of the detailed fluid models will be handled using online servers, with results passed to the tool. Newly-developed artificial intelligence will help interpret the results and provide users with tailored advice on how best to arrange their space to strike the best balance between safety and practicality.
Professor Andrea Cammarano, of the University of Glasgow’s James Watt School of Engineering, is RELIANT’s principal investigator.
He said: “Social distancing and the use of masks are two of the most effective measures in helping prevent the spread of COVID-19. While vaccines are rolling out around the world, it’s likely that we will still need to maintain some level of social distancing for quite some time into the future.
“In the meantime, however, we still need to share indoor spaces with each other in places like schools, supermarkets and gyms. Businesses, too, need to be able to stay open wherever possible to keep the economy running.
“Currently, there’s no unified system to help people decide how best to minimise the risk of infection indoors. Our hope is that RELIANT will provide an easy-to-use platform to help anyone who has a responsibility for health and safety in an indoor space to keep people safe, both while we’re dealing with COVID-19 and for any similar pandemics we might face in coming years.”
Researchers from the Universities of Cambridge and Strathclyde, Imperial College London and Queen Mary University of London are all contributing to RELIANT. Many of the partners are also contributing their expertise to other modelling projects, including the Royal Society’s Rapid Assistance in Modelling the Pandemic (RAMP) initiative, and will help integrate some of the outcomes of those projects into RELIANT.
RELIANT is supported by funding from the Engineering and Physical Sciences Research Council (EPSRC) and the Medical Research Council (MRC) through UKRI’s COVID-19 rolling call.
The RELIANT team will also receive research support from partners at Cambridge University’s Hospital of Addenbrooks, the University of Genova, and VisUp.