Modelling Airborne Transmission of SARS-CoV-2 Using CARA: Risk Assessment for Enclosed Spaces
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The COVID-19 pandemic has highlighted the need for a proper risk assessment of respiratory pathogens in indoor settings. This paper documents the COVID Airborne Risk Assessment methodology, to assess the potential exposure of airborne SARS-CoV-2 viruses, with an emphasis on virological and immunological factors in the quantification of the risk. The model results from a multidisciplinary approach linking physical, mechanical and biological domains, enabling decision makers or facility managers to assess their indoor setting. The model was benchmarked against clinical data, as well as two real-life outbreaks, showing good agreement. A probability of infection is computed in several everyday-life settings and with various mitigation measures. The importance of in airborne transmission is confirmed: 20% of infected hosts can emit approximately two orders of magnitude more viral-containing particles. The use of masks provides a fivefold reduction in viral emissions. Natural ventilation strategies are very effective to decrease the concentration of virions, although periodic venting strategies are not ideal in certain settings. Although vaccination is an effective measure against hospitalization, their effectiveness against transmission is not optimal, hence non-pharmaceutical interventions (ventilation, masks) should be actively supported. We also propose a critical threshold to define an acceptable risk level.
Henriques A, Jia W, Aleixo L, Mounet N, Fontana L, Simniceanu A J R Soc Interface. 2025; 22(223):20240740.
PMID: 39999884 PMC: 11858786. DOI: 10.1098/rsif.2024.0740.
Spiteri S, Marino F, Girolamini L, Pascale M, Derelitto C, Caligaris L Pathogens. 2024; 13(11).
PMID: 39599574 PMC: 11597229. DOI: 10.3390/pathogens13111022.
Shen X, Xu Y, Ye Y, Huai S, Wu P, Huang J BMC Ophthalmol. 2024; 24(1):392.
PMID: 39227827 PMC: 11373106. DOI: 10.1186/s12886-024-03664-7.
On modelling airborne infection risk.
Drossinos Y, Stilianakis N R Soc Open Sci. 2024; 11(7):231976.
PMID: 39050731 PMC: 11265909. DOI: 10.1098/rsos.231976.
AI-Enhanced Tools and Strategies for Airborne Disease Prevention in Cultural Heritage Sites.
Greco E, Gaetano A, De Spirt A, Semeraro S, Piscitelli P, Miani A Epidemiologia (Basel). 2024; 5(2):267-274.
PMID: 38920753 PMC: 11203220. DOI: 10.3390/epidemiologia5020018.