A quantitative risk estimation platform for indoor aerosol transmission of COVID-19

Abstract

AbstractAerosol transmission has played a significant role in the transmission of COVID-19 disease worldwide. We developed a COVID-19 aerosol transmission risk estimation platform to better understand how key parameters associated with indoor spaces and infector emissions affect inhaled deposited dose of aerosol particles that convey the SARS-CoV-2 virus. The model calculates the concentration of size-resolved, virus-laden aerosol particles in well-mixed indoor air challenged by emissions from an index case(s). The model uses a mechanistic approach, accounting for particle emission dynamics, particle deposition to indoor surfaces, ventilation rate, and single-zone filtration. The novelty of this model relates to the concept of “inhaled & deposited dose” in the respiratory system of receptors linked to a dose-response curve for human coronavirus HCoV-229E. We estimated the volume of inhaled & deposited dose of particles in the 0.5 to 4 μm range expressed in picoliters (pL) in a well-documented COVID-19 outbreak in restaurant X in Guangzhou China. We anchored the attack rate with the dose-response curve of HCoV-229E which provides a preliminary estimate of the average SARS-CoV-2 dose per person, expressed in plaque forming units (PFUs). For a reasonable emission scenario, we estimate approximately three PFU per pL deposited, yielding roughly 10 PFUs deposited in the respiratory system of those infected in Restaurant X. To explore the platform’s utility, we tested the model with four COVID-19 outbreaks. The risk estimates from the model fit reasonably well with the reported number of confirmed cases given available metadata from the outbreaks and uncertainties associated with model assumptions.Practical ImplicationsThe model described in this paper is more mechanistic in nature than standard probabilistic models that fail to account for particle deposition to indoor materials, filtration, and deposition of particles in the respiratory system of receptors. As such, it provides added insights into how building-related factors affect relative infection risk associated with inhaled deposited dose. An online version of this mechanistic aerosol risk estimation platform is available at Safeairspaces.com. Importantly, the modular nature of this approach allows for easy updates when new information is available regarding dose-response relationships for SARS-CoV-2 or its variants.