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. 2020 Dec:145:106112.
doi: 10.1016/j.envint.2020.106112. Epub 2020 Sep 6.

Quantitative assessment of the risk of airborne transmission of SARS-CoV-2 infection: Prospective and retrospective applications

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Quantitative assessment of the risk of airborne transmission of SARS-CoV-2 infection: Prospective and retrospective applications

G Buonanno et al. Environ Int. 2020 Dec.

Abstract

Airborne transmission is a recognized pathway of contagion; however, it is rarely quantitatively evaluated. The numerous outbreaks that have occurred during the SARS-CoV-2 pandemic are putting a demand on researchers to develop approaches capable of both predicting contagion in closed environments (predictive assessment) and analyzing previous infections (retrospective assessment). This study presents a novel approach for quantitative assessment of the individual infection risk of susceptible subjects exposed in indoor microenvironments in the presence of an asymptomatic infected SARS-CoV-2 subject. The application of a Monte Carlo method allowed the risk for an exposed healthy subject to be evaluated or, starting from an acceptable risk, the maximum exposure time. We applied the proposed approach to four distinct scenarios for a prospective assessment, highlighting that, in order to guarantee an acceptable risk of 10-3 for exposed subjects in naturally ventilated indoor environments, the exposure time could be well below one hour. Such maximum exposure time clearly depends on the viral load emission of the infected subject and on the exposure conditions; thus, longer exposure times were estimated for mechanically ventilated indoor environments and lower viral load emissions. The proposed approach was used for retrospective assessment of documented outbreaks in a restaurant in Guangzhou (China) and at a choir rehearsal in Mount Vernon (USA), showing that, in both cases, the high attack rate values can be justified only assuming the airborne transmission as the main route of contagion. Moreover, we show that such outbreaks are not caused by the rare presence of a superspreader, but can be likely explained by the co-existence of conditions, including emission and exposure parameters, leading to a highly probable event, which can be defined as a "superspreading event".

Keywords: Coronavirus; Indoor; SARS-CoV-2 (COVID-19) assessment; Ventilation; Virus airborne transmission.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

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Graphical abstract
Fig. 1
Fig. 1
Trends of quanta concentration (a), dose of quanta (b), and probability of infection (c) as a function of time (here shown for 2 h of exposure) and quanta emission rates resulting from the Monte Carlo simulation for exposure scenario D with an AER = 0.5 h−1. The ERq values were reported as percentiles.
Fig. 2
Fig. 2
Probability density functions of ERq (pdfERq, expressed as PERq), probability of infection (pdfP, expressed as PI(ERq)), and individual infection risk (pdfR, expressed as R(ERq)) at t = 120 min for the illustrative example reported in Fig. 1 (exposure scenario D with an air exchange rate of 0.5 h−1). The relative frequency PERq is here graphed as 99 equally spaced log(ERq) values (from 1st to 99th percentiles) adopting the log-normal probability density functions of ERq (pdfERq).
Fig. 3
Fig. 3
Relationship between time of exposure and individual risk (R) as a function of the air exchange rate (0.5 h−1, 3 h−1, and 10 h−1) for the exposure scenarios investigated in the prospective approach and summarized in Table 1.
Fig. 4
Fig. 4
Quanta concentration (n) and probability of infection (PI) evaluated for the retrospective cases applied at the documented outbreaks at (a) the restaurant in Guangzhou (for ERq = 61 quanta h−1) and (b) the Skagit Valley choir (for ERq = 341 quanta h−1).

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