Predictive and retrospective modelling of airborne infection risk using monitored carbon dioxide
File(s)
Published version
Author(s)
Burridge, Henry
Fan, Shewei
Jones, Roderic
Noakes, Cath
Linden, Paul
Type
Journal Article
Abstract
The risk of long range, herein ‘airborne’, infection needs to be better understood and is especially urgent during
the COVID-19 pandemic. We present a method to determine the relative risk of airborne transmission that can be
readily deployed with either modelled or monitored CO2 data and occupancy levels within an indoor space. For spaces
regularly, or consistently, occupied by the same group of people, e.g. an open-plan office or a school classroom, we
establish protocols to assess the absolute risk of airborne infection of this regular attendance at work or school. We
present a methodology to easily calculate the expected number of secondary infections arising from a regular attendee
becoming infectious and remaining pre/asymptomatic within these spaces. We demonstrate our model by calculating
risks for both a modelled open-plan office and by using monitored data recorded within a small naturally ventilated
office. In addition, by inferring ventilation rates from monitored CO2 we show that estimates of airborne infection can be
accurately reconstructed; thereby offering scope for more informed retrospective modelling should outbreaks occur in
spaces where CO2 is monitored. Well ventilated spaces appear unlikely to significantly contribute to airborne infection.
However, even moderate changes to the conditions within the office, or new variants of the disease, typically results in
more troubling predictions.
the COVID-19 pandemic. We present a method to determine the relative risk of airborne transmission that can be
readily deployed with either modelled or monitored CO2 data and occupancy levels within an indoor space. For spaces
regularly, or consistently, occupied by the same group of people, e.g. an open-plan office or a school classroom, we
establish protocols to assess the absolute risk of airborne infection of this regular attendance at work or school. We
present a methodology to easily calculate the expected number of secondary infections arising from a regular attendee
becoming infectious and remaining pre/asymptomatic within these spaces. We demonstrate our model by calculating
risks for both a modelled open-plan office and by using monitored data recorded within a small naturally ventilated
office. In addition, by inferring ventilation rates from monitored CO2 we show that estimates of airborne infection can be
accurately reconstructed; thereby offering scope for more informed retrospective modelling should outbreaks occur in
spaces where CO2 is monitored. Well ventilated spaces appear unlikely to significantly contribute to airborne infection.
However, even moderate changes to the conditions within the office, or new variants of the disease, typically results in
more troubling predictions.
Date Issued
2022-05-01
Date Acceptance
2021-08-13
Citation
Indoor and Built Environment, 2022, 31 (5), pp.1363-1380
ISSN
1016-4901
Publisher
SAGE Publications
Start Page
1363
End Page
1380
Journal / Book Title
Indoor and Built Environment
Volume
31
Issue
5
Copyright Statement
© The Author(s) 2021. This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
License URL
Sponsor
Health & Safety Executive
Health & Safety Executive
Grant Number
1.11.4.3786
43070015715
Subjects
Science & Technology
Technology
Life Sciences & Biomedicine
Construction & Building Technology
Engineering, Environmental
Public, Environmental & Occupational Health
Engineering
Infection modelling
Airborne infection risk
Monitored CO2
COVID-19
Coronavirus SAR-CoV-2
VENTILATION
TRANSMISSION
Building & Construction
0905 Civil Engineering
1202 Building
Publication Status
Published
Date Publish Online
2021-09-28