Amid the rise in Covid-19 infections in South Africa, a joint team from the University of Johannesburg (UJ) Faculty of Engineering and the Perinatal HIV Research Unit (PHRU) at the University of the Witwatersrand has developed an interdisciplinary  research project that seeks to estimate the time evolving probability of infection using droplets and surface films in selected environments.

UJ Faculty of Engineering physics professor Simon Connell says the project was partly borne out of the fact that there are many situations where it is not possible to apply the 2 m physical distancing rule.

“We need to understand what happens to the time evolution of the virus in droplets entrained in fluid flows in enclosed spaces.

“Furthermore, it is important to understand what the effects of engineered medical interventions are and how can they be optimised,” he notes.

The interdisciplinary team are developing tools that are able to predict the evolving infectiousness of Covid-19-containing respiratory droplets, after they are coughed or sneezed out.

Tuberculosis (TB) has the same respiratory droplet transmission as Covid-19.  

“With our modern data intensive approach, we are able to collect, quantify and compare data on the droplet infectiousness (airborne and surface contamination) based on local environmental conditions,” explains Connell.

Dr Muaaz Bhamjee, also of UJ, explains that this technology is especially needed in scenarios where adhering to physical distancing is sometimes challenging.

“This approach uses laser point cloud scanning to establish three-dimensional geometries, supplemented by data of materials for surfaces, surface temperatures and local flow streams near sources or sinks of flow.

“This is then fed into a sophisticated computer model that can predict the level of infectiousness in the air.  We are linking with the surveyors in UJ’s Department of Mining Engineering to provide cutting-edge laser scanning capacity,” says Bhamjee.   

PHRU CEO Professor Neil Martinson points out that this model could be deployed in places where people congregate, such as schools, universities, taxi ranks or inside minibus taxis, as well as in clinics, hospitals, mines and even care homes.

“Accurate prediction of the infection risk in these places will allow us to model environmental modifications – such as extraction fans, ultraviolet light and strategically placed air vents − that could prevent the transmission of both Covid-19 and TB,” he states.