Viral Aerosol Concentration Characterization and Detection in Bounded Environments

TL;DR

This paper models viral aerosol dispersion in enclosed spaces and evaluates a detection system using air samplers and biosensors, providing analytical expressions and simulations to improve indoor viral detection accuracy.

Contribution

It introduces a novel analytical model for viral aerosol concentration in bounded environments and assesses a detection system's performance through simulations.

Findings

Closed-form expression for virus concentration in rooms

Detection system's miss-detection probability depends on sampling volume and time

System effectively detects viruses in indoor environments

Abstract

Viral spread has been intermittently threatening human life over time. Characterizing the viral concentration and modelling the viral transmission are, therefore, considered major milestones for enhancing viral detection capabilities. This paper addresses the problem of viral aerosol detection based on the exhaled breath in a bounded environment, e.g., a bounded room. The paper models the exhaled breath as a cloud which is emitted through the room continuously, and analyzes the temporal-spatial virus concentration by accounting for partial absorption and reflection at each side of the room. The paper first derives a closed form expression of the temporal-spatial virus concentration. It then considers the deployment of a receiver composed of an air sampler and a bio-sensor to detect the viral existence of a specific virus. We, therefore, assess the detection capabilities of the proposed system via evaluating the viral miss-detection probability as a function of the sampling volume and the detection time-instance at the receiver side. Our numerical simulations verify the validity of the analytical results, and illustrate the ability of the proposed system to detect viruses in indoor environments. The results further characterize the impacts of several system parameters on the miss-detection probability.