Association of the infection probability of COVID-19 with ventilation rates in confined spaces
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Association of the infection probability of COVID-19 with ventilation rates in confined spaces
1. Department of Building Science, School of Architecture, Tsinghua University, Beijing 100084, China 2. Beijing Key Laboratory of Indoor Air Quality Evaluation and Control, Tsinghua University, Beijing 100084, China
Abstract
Keywords
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.
COVID-19,
1
Introduction
E-mail: [email protected]
SARS-CoV-2, ventilation, infection probability, Wells–Riley equation
Article History Received: 11 June 2020 Revised: 27 July 2020 Accepted: 27 July 2020 © Tsinghua University Press and Springer-Verlag GmbH Germany, part of Springer Nature 2020
the easier spread of SARS-CoV-2 in confined spaces. The Wells–Riley equation is a classic model for quantifying the risk associated with airborne transmission of respiratory diseases (Riley et al. 1978). It has been used to demonstrate that some building factors (particularly the ventilation rate) are important removal mechanisms for airborne infectious agents (Escombe et al. 2007). In addition, a report by WHO suggested that insufficient ventilation increases disease transmission (Chartier et al. 2009). Therefore, ensuring a sufficient ventilation rate for offices, classrooms, and public transport is essential to reduce the potential risk of infection in these confined spaces, which is extremely important for daily life. In this study, we employed the Wells–Riley equation to estimate the association between the infection probability and ventilation rate, where the quantum generation rate (q) is a critical parameter. The value of q of a COVID-19 infector is currently not well established, and we obtained this value based on its fitted correlation with the basic reproductive number (R0). We then estimated the association b
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