A population framework for predicting the proportion of people infected by the far-field airborne transmission of SARS-CoV-2 indoors

Christopher Iddon; Benjamin Jones; Patrick Sharpe; Muge Cevik; Shaun Fitzgerald

doi:10.1016/j.buildenv.2022.109309

A population framework for predicting the proportion of people infected by the far-field airborne transmission of SARS-CoV-2 indoors

Build Environ. 2022 Aug 1:221:109309. doi: 10.1016/j.buildenv.2022.109309. Epub 2022 Jun 18.

Authors

Christopher Iddon¹, Benjamin Jones¹, Patrick Sharpe¹, Muge Cevik², Shaun Fitzgerald³

Affiliations

¹ Department of Architecture and Built Environment, University of Nottingham, Nottingham, UK.
² Department of Infection and Global Health, School of Medicine, University of St Andrews, St Andrews, UK.
³ Department of Engineering, Cambridge University, Cambridge, UK.

Abstract

The number of occupants in a space influences the risk of far-field airborne transmission of SARS-CoV-2 because the likelihood of having infectious and susceptible people both correlate with the number of occupants. This paper explores the relationship between occupancy and the probability of infection, and how this affects an individual person and a population of people. Mass-balance and dose-response models determine far-field transmission risks for an individual person and a population of people after sub-dividing a large reference space into 10 identical comparator spaces. For a single infected person, the dose received by an individual person in the comparator space is 10 times higher because the equivalent ventilation rate per infected person is lower when the per capita ventilation rate is preserved. However, accounting for population dispersion, such as the community prevalence of the virus, the probability of an infected person being present and uncertainty in their viral load, shows the transmission probability increases with occupancy and the reference space has a higher transmission risk. Also, far-field transmission is likely to be a rare event that requires a high emission rate, and there are a set of Goldilocks conditions that are just right when equivalent ventilation is effective at mitigating against transmission. These conditions depend on the viral load, because when they are very high or low, equivalent ventilation has little effect on transmission risk. Nevertheless, resilient buildings should deliver the equivalent ventilation rate required by standards as minimum.

Keywords: Aerosols; COVID-19; Relative exposure index; Transmission risk; Ventilation; Viral load.