Imperial College London
Alternate

DrHenryBurridge

Faculty of Engineering, Department of Civil and Environmental Engineering

Senior Lecturer
 
 
 
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Contact

 

+44 (0)20 7594 5201h.burridge Website

 
 
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Assistant

 

Miss Rebecca Naessens +44 (0)20 7594 5990

 
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Location

 

328ASkempton BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Burridge:2022:10.1177/1420326X211043564,
author = {Burridge, HC and Fan, S and Jones, RL and Noakes, CJ and Linden, PF},
doi = {10.1177/1420326X211043564},
journal = {Indoor and Built Environment},
pages = {1363--1380},
title = {Predictive and retrospective modelling of airborne infection risk using monitored carbon dioxide},
url = {http://dx.doi.org/10.1177/1420326X211043564},
volume = {31},
year = {2022}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - 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 contribute significantly to airborne infection. However, even moderate changes to the conditions within the office, or new variants of the disease, typically result in more troubling predictions.
AU  - Burridge,HC
AU  - Fan,S
AU  - Jones,RL
AU  - Noakes,CJ
AU  - Linden,PF
DO  - 10.1177/1420326X211043564
EP  - 1380
PY  - 2022///
SN  - 1420-326X
SP  - 1363
TI  - Predictive and retrospective modelling of airborne infection risk using monitored carbon dioxide
T2  - Indoor and Built Environment
UR  - http://dx.doi.org/10.1177/1420326X211043564
UR  - http://hdl.handle.net/10044/1/91129
VL  - 31
ER  -
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