Modeling airborne transmission of viral genome using computational fluid dynamics simulation: A case study for SARS-CoV-2 virus

Abstract

Predicting indoor air quality during infectious disease conditions relies on models simulating particle materials (PM)/bioaerosols distribution. Understanding the thermo-fluid properties of exhaled air is crucial for comprehending disease transmission dynamics. This study employs a computational fluid dynamics (CFD) model to simulate cough-induced particle dispersion in a closed space. Furthermore, the number of released particles and the presence of SARS-CoV-2 viral genomes by a cough were assessed (in eight COVID-19 patients). According to the CFD model, in the first 30 s of cough, the vertical height and lateral breadth of the particles’ dispersion were up to 138cm and 92cm, respectively. As the distance from the patient's respiratory zone increased, the lateral distribution width of particles expanded, reaching 1.3 m at 2.4 m away. Larger droplets (> 62.5µ) were deposited at shorter distances, while smaller particles remained airborne longer. The comparison of experimental and simulated results focused on particle dispersion at specific distances from the patient, particularly in the 2.5µ range. The distribution pattern of PM_2.5 and PM₁₀ at a distance of 1 and 2 m for women, not men, is similar to the distribution pattern of PM in CFD modeling. Viral genome detection was more prevalent in particles near the left side of the body, especially within the first 20 min post-cough, exhibiting a correlation with CFD predictions.