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dc.contributor.authorAganovic, Amar
dc.contributor.authorKurnitski, Jarek
dc.contributor.authorWargocki, Pawel
dc.date.accessioned2024-10-04T10:24:43Z
dc.date.available2024-10-04T10:24:43Z
dc.date.issued2024-04-05
dc.description.abstractThe Wells-Riley model is extensively used for retrospective and prospective modelling of the risk of airborne transmission of infection in indoor spaces. It is also used when examining the efficacy of various removal and deactivation methods for airborne infectious aerosols in the indoor environment, which is crucial when selecting the most effective infection control technologies. The problem is that the large variation in viral load between individuals makes the Wells-Riley model output very sensitive to the input parameters and may yield a flawed prediction of risk. The absolute infection risk estimated with this model can range from nearly 0 % to 100 % depending on the viral load, even when all other factors, such as removal mechanisms and room geometry, remain unchanged. We therefore propose a novel method that removes this sensitivity to viral load. We define a quanta-independent maximum absolute before-after difference in infection risk that is independent of quanta factors like viral load, physical activity, or the dose-response relationships. The input data needed for a non-steady-state calculation are just the removal rates, room volume, and occupancy duration. Under steady-state conditions the approach provides an elegant solution that is only dependent on removal mechanisms before and after applying infection control measures. We applied this method to compare the impact of relative humidity, ventilation rate and its effectiveness, filtering efficiency, and the use of ultraviolet germicidal irradiation on the infection risk. The results demonstrate that the method provides a comprehensive understanding of the impact of infection control strategies on the risk of airborne infection, enabling rational decisions to be made regarding the most effective strategies in a specific context. The proposed method thus provides a practical tool for mitigation of airborne infection risk.en_US
dc.identifier.citationAganovic, Kurnitski, Wargocki. A quanta-independent approach for the assessment of strategies to reduce the risk of airborne infection. Science of the Total Environment. 2024;927en_US
dc.identifier.cristinIDFRIDAID 2264683
dc.identifier.doi10.1016/j.scitotenv.2024.172278
dc.identifier.issn0048-9697
dc.identifier.issn1879-1026
dc.identifier.urihttps://hdl.handle.net/10037/35051
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.relation.journalScience of the Total Environment
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2024 The Author(s)en_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0en_US
dc.rightsAttribution 4.0 International (CC BY 4.0)en_US
dc.titleA quanta-independent approach for the assessment of strategies to reduce the risk of airborne infectionen_US
dc.type.versionpublishedVersionen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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Attribution 4.0 International (CC BY 4.0)
Med mindre det står noe annet, er denne innførselens lisens beskrevet som Attribution 4.0 International (CC BY 4.0)