Logo image
A Quantitative Risk Estimation Platform for Indoor Aerosol Transmission of COVID‐19
Journal article   Open access   Peer reviewed

A Quantitative Risk Estimation Platform for Indoor Aerosol Transmission of COVID‐19

Hooman Parhizkar, Kevin G. Van Den Wymelenberg, Charles N. Haas and Richard L. Corsi
Risk analysis, v 42(9), pp 2075-2088
Sep 2022
PMID: 34713463
url
https://doi.org/10.1111/risa.13844View
Published, Version of Record (VoR)CC BY-NC V4.0 Open

Abstract

aerosol particles COVID‐19 filtration infection SARS‐CoV‐2 ventilation
Aerosol transmission has played a significant role in the transmission of COVID‐19 disease worldwide. We developed a COVID‐19 aerosol transmission risk estimation model 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 0.5–4 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 model's utility, we tested it 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.

Metrics

11 Record Views
29 citations in Scopus

Details

UN Sustainable Development Goals (SDGs)

This publication has contributed to the advancement of the following goals:

#3 Good Health and Well-Being

InCites Highlights

Data related to this publication, from InCites Benchmarking & Analytics tool:

Collaboration types
Domestic collaboration
Web of Science research areas
Mathematics, Interdisciplinary Applications
Public, Environmental & Occupational Health
Social Sciences, Mathematical Methods
Logo image