Khaliq, K.A. orcid.org/0000-0003-3582-9313, Mohamad, S. orcid.org/0000-0001-5235-3121, Edwards, A.J. orcid.org/0000-0001-5313-8490 et al. (5 more authors) (2024) Environmental data monitoring and infection risks in UK care-homes in the context of COVID-19. Building and Environment, 250. 111174. ISSN 0360-1323
Abstract
The COVID-19 pandemic drew attention to the critical role of building ventilation as a measure for controlling infection transmission. With the substantial number of COVID-19 outbreaks a in care homes worldwide, the effectiveness of ventilation is an important consideration for infection control and wider exposure to indoor air pollutants. In this study, we used IoTbased sensors in two residential care homes to evaluate ventilation in various areas, including bedrooms, corridors, and communal spaces. Our monitoring focused on carbon dioxide (CO2) levels as a proxy for ventilation, as well as temperature and humidity, during the spring of 2022. We also developed a ventilation model using the software CONTAM and coupled it with an infection risk model to assess airborne transmission risks under different weather and occupancy conditions. Our results suggest that ventilation is generally adequate based on UK COVID-19 guidelines at the time, with CO2 below 800ppm for the majority of the time, and opening windows in communal spaces in elderly care environments can help preserve indoor ventilation during periods of high occupancy. However, modelling data suggests that low CO2 values may be indicative of low occupancy in many spaces and therefore ventilation rates may not be sufficient to mitigate infection transmission. Encouraging positive ventilation behaviours in staff and residents, potentially supported by visible CO2 monitors, and taking additional precautions such as using air cleaners, enabling additional window openings or staff wearing masks during outbreaks and periods of high disease prevalence is likely to be beneficial for resident and staff health.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2024 The Author(s). This is an open access article under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. |
Keywords: | COVID-1; Long term monitoring CO2; Indoor environment; IAQ; Data visualisation |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Civil Engineering (Leeds) The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Healthcare (Leeds) > Nursing Adult (Leeds) |
Funding Information: | Funder Grant number NIHR National Inst Health Research NIHR132197 NIHR National Inst Health Research Not Known |
Depositing User: | Symplectic Publications |
Date Deposited: | 10 Jan 2024 15:03 |
Last Modified: | 18 Oct 2024 13:55 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.buildenv.2024.111174 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:207425 |