Gesundheit! Clark researchers use simulated sneezes in NSF-funded COVID-19 study

The COVID-19 virus is mainly spread through respiratory droplets or small particles that are produced when an infected person coughs, sneezes, talks, or breathes. While the aerodynamics of such droplets have been the main focus of many studies, little is known about the journey of these expelled droplets and where they come to rest.

“The spread is mostly caused by inhaling these droplets, but strangely enough there isn’t much information about where these droplets end up landing on surfaces,” says Brian Chang, postdoctoral researcher at Clark University.

To better understand how mucosalivary droplets are distributed on surfaces after expiratory events, Chang spent the past several months working alongside Physics Professor Arshad Kudrolli, Ram Sharma ’19, M.A. ’20, and Trinh Huynh ’21 to study how these particles travel through the air.

On Thursday, Chang will present the team’s findings during a Zoom presentation, “The fate of a mucosalivary droplet: Lessons from a synthetic sneeze,” as part of the Fall 2020 Physics Colloquium.

“We will go over the science of the droplets and what trajectories they take and what kind of random interactions they might have with each other as they fall and land on surfaces,” Chang says. “We created a mechanical device that sprays the droplets and we matched the droplet size and the speed at which they’re being expelled to actual human sneezes.”

The study, funded by a $200,000 grant for Rapid Response Research from the National Science Foundation Division of Materials Research, involved using the spray device inside a 3D-printed mannequin face to expel fluorescent-tagged mucosaliva — made from a combination of water and mucin (large, heavily glycosylated proteins that give mucus its slimy feel) — to imitate a human sneeze. The researchers used a high-speed camera to track the mucosaliva, examining the puff cloud dynamics of the droplets, landing times, and spatial distribution on a flat surface.

The mannequin was also outfitted with a standard medical mask to determine how effective face masks are at reducing droplet dispersal.

“What we found is the six-foot guideline [for social distancing] is effective, but it’s not the only guideline we should be following. There is a time guideline that we should follow, as well,” Chang says. “For a person who is 5 feet, 5 inches tall, once these droplets get expelled it can take them about five seconds to reach the ground.”

If there is any airflow, Chang says, droplets may linger longer in the air.

The researchers also found that standard medical masks are very effective at stopping the spread of droplets — reducing the dispersed mucosaliva by a factor of at least 100 compared to the dispersal when unmasked.

“Masks are so effective, even if they aren’t perfect,” Chang says. “That was our most important finding.”

In the future, the team plans to study droplet dispersal from more subtle expiratory events, such as talking. Chang adds that he also plans to conduct tests with other types of masks, including cloth face coverings and N95 respirators. In addition to quantifying the effectiveness of masks, Chang says the research can be used by others who are creating predictive models of the pandemic.

“With our model implemented in different scenarios, people can start predicting how fast this disease can spread,” he says.

Chang’s presentation will be held on Thursday from noon to 1 p.m. via Zoom. More information and a link can be found here.