This is further evidence of the importance of wearing masks, which would trap particles in this critical range.
The team of engineers from the UC San Diego Jacobs School of Engineering, University of Toronto and Indian Institute of Science are all experts in the aerodynamics and physics of droplets for applications including propulsion systems, combustion or thermal sprays. They turned their attention and expertise to droplets released when people sneeze, cough or talk when it became clear that COVID-19 is spread through these respiratory droplets. They applied existing models for chemical reactions and physics principles to droplets of a salt water solution--saliva is high in sodium chloride--which they studied in an ultrasonic levitator to determine the size, spread, and lifespan of these particles in various environmental conditions.
Many current pandemic models use fitting parameters to be able to apply the data to an entire population. The new model aims to change that.
"Our model is completely based on "first principles" by connecting physical laws that are well understood, so there is next to no fitting involved," said Swetaprovo Chaudhuri, professor at University of Toronto and a co-author. "Of course, we make idealized assumptions, and there are variabilities in some parameters, but as we improve each of the submodels with specific experiments and including the present best practices in epidemiology, maybe a first principles pandemic model with high predictive capability could be possible."
There are limitations to this new model, but the team is already working to increase the model's versatility.
"Our next step is to relax a few simplifications and to generalize the model by including different modes of transmission," said Saptarshi Basu, professor at the Indian Institute of Science and a co-author. "A set of experiments are also underway to investigate the respiratory droplets that settle on commonly touched surfaces."