We are investigating how infectious viral disease such as influenza and COVID-19 spread with experiments and physical modeling.
A link to Brian Chang's presentation on our group's research can be found on YouTube. Also, see the ClarkNow press article which discussed his research.
A preprint is out on our work:
Aerial mucosalivary droplet dispersal distributions with implications for disease mitigation, Brian Chang, Ram Sudhir Sharma, Trinh Huynh, and Arshad Kudrolli
Abstract: We investigate mucosalivary dispersal and deposition on horizontal surfaces corresponding to human exhalations with physical experiments under still-air conditions. Synthetic fluorescence tagged sprays with size and speed distributions comparable to human sneezes are observed with high-speed imaging. We show that while some larger droplets follow parabolic trajectories, smaller droplets stay aloft for several seconds and settle slowly with speeds consistent with a buoyant cloud dynamics model. The net deposition distribution is observed to become correspondingly broader as the source height H is increased, ranging from sitting at a table to standing upright. We find that the deposited mucosaliva decays exponentially in front of the source, after peaking at distance x = 0.71m when H = 0.5m, and x = 0.56m when H=1.5m, with standard deviations \approx 0.5m. Greater than 99% of the mucosaliva is deposited within x = 2\,m, with faster landing times further from the source. We then demonstrate that a standard nose and mouth mask reduces the mucosaliva dispersed by a factor of at least a hundred compared to the peaks recorded when unmasked.
medrxiv: DOI: 10.1101/2020.10.15.20213314v1
This work is funded by NSF Grant # 2030307 RAPID: Predicting Coronavirus Disease (COVID-19) Impact with Multiscale Contact and Transmission Mitigation to develop an understanding of spatiotemporal mucosalivary droplet distribution required to develop infectious spread and mitigation models.