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

Ciara A. Higham , Martín López-García , Catherine J. Noakes , Emma Tidswell , Louise Fletcher
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Abstract

Background

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.

Methods

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.

Results

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.

Conclusion

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.
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Corrigendum to “Ventilation characteristics in a hospital where a COVID-19 outbreak occurred in the winter of 2020” [Indoor Environ. 2 (2025) 100065] Implementing Bayesian inference on a stochastic CO2-based grey-box model CO2 levels and SARS-CoV-2 transmission in public schools: A retrospective cohort study in Montreal (Canada) Cognition, economic decision-making, and physiological response to carbon dioxide Corrigendum to “Towards equitable and sustainable indoor air quality guidelines – A perspective on mandating indoor air quality for public buildings” [Indoor Environ. 2 1 (2025) 100070]
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