Are Runners More Prone to Become Infected with COVID-19? An Approach from the Raindrop Collisional Model

Area of Science:

• Fluid dynamics
• Aerosol science
• Epidemiology

Background:

• COVID-19 transmission primarily occurs via respiratory droplets from infected individuals.
• A common belief suggests close-proximity runners face higher infection risk due to stronger exhalation and droplet collision.
• The physics of droplet-runner interaction requires detailed examination beyond simple assumptions.

Purpose of the Study:

• To investigate the relationship between runner velocity and the probability of colliding with airborne respiratory droplets.
• To challenge the generalized assumption that closer proximity always equates to higher droplet exposure risk for runners.

Main Methods:

• Employed computational fluid dynamics (CFD) simulations.
• Utilized a raindrop collisional model to analyze droplet-runner interactions.
• Examined the effect of varying runner velocities on droplet collision efficiency.

Main Results:

• The probability of collision with respiratory droplets does not consistently increase with runner velocity.
• A specific velocity threshold exists where droplet collision efficiency reaches a maximum.
• Beyond this threshold, the efficiency of collision with respiratory droplets decreases as velocity increases.

Conclusions:

• The assumption that increased running speed directly correlates with higher COVID-19 risk from respiratory droplets is questionable.
• Runner velocity plays a complex role in droplet exposure, with an optimal speed for collision efficiency.
• Findings suggest a need for nuanced understanding of transmission dynamics in dynamic environments like running.