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Research Article

Association of the infection probability of COVID-19 with ventilation rates in confined spaces

Hui Dai1, Bin Zhao1,2( )
Department of Building Science, School of Architecture, Tsinghua University, Beijing 100084, China
Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
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Abstract

A growing number of cases have proved the possibility of airborne transmission of the coronavirus disease 2019 (COVID-19). Ensuring an adequate ventilation rate is essential to reduce the risk of infection in confined spaces. In this study, we estimated the association between the infection probability and ventilation rates with the Wells-Riley equation, where the quantum generation rate (q) by a COVID-19 infector was obtained using a reproductive number-based fitting approach. The estimated q value of COVID-19 is 14-48 h-1. To ensure an infection probability of less than 1%, a ventilation rate larger than common values (100-350 m3/h per infector and 1200-4000 m3/h per infector for 0.25 h and 3 h of exposure, respectively) is required. If the infector and susceptible person wear masks, then the ventilation rate ensuring a less than 1% infection probability can be reduced to a quarter respectively, which is easier to achieve by the normal ventilation mode applied in typical scenarios, including offices, classrooms, buses, and aircraft cabins. Strict preventive measures (e.g., wearing masks and preventing asymptomatic infectors from entering public spaces using tests) that have been widely adopted should be effective in reducing the risk of infection in confined spaces.

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Building Simulation
Pages 1321-1327

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Cite this article:
Dai H, Zhao B. Association of the infection probability of COVID-19 with ventilation rates in confined spaces. Building Simulation, 2020, 13(6): 1321-1327. https://doi.org/10.1007/s12273-020-0703-5

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Received: 11 June 2020
Accepted: 27 July 2020
Published: 04 August 2020
© Tsinghua University Press and Springer-Verlag GmbH Germany, part of Springer Nature 2020