A Quantitative Microbial Risk Assessment (QMRA) framework for exposure from toilet flushing using experimental aerosol concentration measurements

• Published in: Indoor environments 2025-03, Vol.2 (1), p.100069, Article 100069
• Main Authors: Higham, Ciara A., López-García, Martín, Noakes, Catherine J., Tidswell, Emma, Fletcher, Louise
• Format: Article
• Language: English
• Subjects: Aerosols; Infection risk; QMRA; Toilet
• ISSN: 2950-3620; 2950-3620
• DOI: 10.1016/j.indenv.2024.100069

Flushing a toilet generates aerosols potentially containing microorganisms, serving as a transmission route for pathogens, notably gastrointestinal and respiratory infections. Despite identification of aerosols and positive microbial sampling, there is a lack of quantitative assessments linking aerosol generation to infection risk in toilet settings. We develop a framework to evaluate the infection risk to a second susceptible individual using a shared toilet following faecal shedding and flush aerosolisation by an infected individual. Experimental measurements of particle concentrations from a toilet flush in a controlled chamber are combined with a model using Quantitative Microbial Risk Assessment (QMRA) methods. We demonstrate the approach for SARS-CoV-2 and norovirus, examining model sensitivity and how adding cubicle space and varying occupancy times affect risk. The model suggests non-negligible infection risk from the toilet plume, particularly for pathogens with higher concentrations in faeces. The model suggests norovirus could have a 2 times greater maximum infection risk than SARS-CoV-2. Mean and median risks for all scenarios decreased when the second individual entered 60 s post-flush compared to 0 s. Occupancy times had less impact on risk compared to the timing of entry post-flush. To mitigate infection risk from shared toilets, ventilating the room before entering is crucial. Allowing time between toilet usages may be more effective compared to reducing occupancy times. Models provide valuable insights into relative impacts of measures and comparison between pathogens, but improved quantitative data is needed, particularly in higher risk scenarios (e.g. hospitals, public events), to quantify absolute risks. [Display omitted]