Recent studies have indicated that COVID-19 is an airborne disease, which has driven conservative social distancing and widescale usage of face coverings. Airborne virus transmission occurs through droplets formed during respiratory events (breathing, speaking, coughing, and sneezing) associated with the airflow through a network of nasal and buccal passages. The airflow interacts with saliva/mucus films where droplets are formed and dispersed, creating a route to transmit SARS-CoV-2. Here, we present a series of numerical simulations to investigate droplet dispersion from a sneeze while varying a series of human physiological factors that can be associated with illness, anatomy, stress condition, and sex of an individual. The model measures the transmission risk utilizing an approximated upper respiratory tract geometry for the following variations: (1) the effect of saliva properties and (2) the effect of geometric features within the buccal/nasal passages. These effects relate to natural human physiological responses to illness, stress, and sex of the host as well as features relating to poor dental health. The results find that the resulting exposure levels are highly dependent on the fluid dynamics that can vary depending on several human factors. For example, a sneeze without flow in the nasal passage (consistent with congestion) yields a 300% rise in the droplet content at 1.83 m (≈6 ft) and an increase over 60% on the spray distance 5 s after the sneeze. Alternatively, when the viscosity of the saliva is increased (consistent with the human response to illness), the number of droplets is both fewer and larger, which leads to an estimated 47% reduction in the transmission risk. These findings yield novel insight into variability in the exposure distance and indicate how physiological factors affect transmissibility rates. Such factors may partly relate to how the immune system of a human has evolved to prevent transmission or be an underlying factor driving superspreading events in the COVID-19 pandemic.
All Science Journal Classification (ASJC) codes
- Computational Mechanics
- Condensed Matter Physics
- Mechanics of Materials
- Mechanical Engineering
- Fluid Flow and Transfer Processes