A Quantitative Risk Estimation Platform for Indoor Aerosol Transmission of COVID‐19
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Abstract
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.
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SciScore for 10.1101/2021.03.05.21252990: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:This is meant to help potential users of the screening model platform to develop a practical understanding of its capabilities and limitations. The section uses the platform to simulate four well-known COVID-19 outbreaks as a means to explore its utility and generalizability. 3.1. Case 1. Bus ride in Eastern China: People who rode one …
SciScore for 10.1101/2021.03.05.21252990: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:This is meant to help potential users of the screening model platform to develop a practical understanding of its capabilities and limitations. The section uses the platform to simulate four well-known COVID-19 outbreaks as a means to explore its utility and generalizability. 3.1. Case 1. Bus ride in Eastern China: People who rode one bus to a worship event and back, in which there was at least one confirmed COVID-19 case, had a statistically significant higher risk of SARS-CoV-2 infection than individuals who rode a different bus to the same event. In the first bus, 23 out of 68 passengers tested positive for COVID-19 while none of the passengers in the second bus were diagnosed with COVID-19 (Shen et al., 2020). Table 2 shows summarizes the inputs used in the risk estimation platform. The air exchange rate for the bus was not published. Using 4 air changes h−1 in the screening model described herein yields the observed 23 infections and 34% infection probability. We were only able to find one published study for which the air exchange rate for a bus was reported. Previously, researchers used sulfur hexafluoride release and decay and reported air exchange rates of 2.6 to 4.6 h−1 for a traveling school bus on its normal route (Rim, Siegel, Spinhirne, Webb, & McDonald-Buller, 2008). This range bounds the air exchange rate of 4 h-1 that yields a model result consistent with disease cases in the outbreak. 3.2. Case 2. Two choir rehearsals in Skagit Valley: Another outbreak event...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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