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Published on: September 27, 2014
Mathematical Modeling of Viral RNA Copies in Indoor Environments: Pre-Processor for Risk Assessment and
Seungjae Gwak1, Seongmin Cho1, David Y H Pui2
1Department of Manufacturing Systems and Design Engineering, Seoul National University of Science and Technology, Seoul, Republic of Korea.
Summary
Accurate airborne viral RNA exposure quantification is improved with a new size-resolved model. This framework enhances infection risk assessment by simulating viral RNA decay and persistence from different exhalation events.
Area of Science:
- Environmental Science
- Epidemiology
- Aerosol Science
Background:
- Accurate quantification of airborne viral RNA is crucial for infection risk assessment and control policies.
- Existing models oversimplify complex droplet physics, limiting accurate size and time-resolved estimates of airborne viral RNA.
- Indoor airborne viral RNA exposure requires sophisticated modeling that accounts for droplet dynamics and environmental factors.
Purpose of the Study:
- To develop a size-resolved framework for computing airborne viral RNA copies.
- To couple saliva-specific evaporation, residue formation, and gravitational settling for improved viral RNA estimation.
- To provide a tool for infection risk assessment and public health decision-making.
Main Methods:
- A size-resolved framework was developed, integrating saliva evaporation, residue formation, and gravitational settling.
- The model computes airborne viral RNA for particles from 1-2000 µm under varied environmental conditions (temperature, humidity, pressure).
- It incorporates particle volume, saliva mass uncertainty, viral load, half-life, exhalation mechanisms, and ventilation effects.
Main Results:
- Viral load and size-resolved airborne lifetime were key factors influencing simulated RNA copy trends.
- Talking was found to dominate the persistence of airborne RNA copies compared to coughing and sneezing.
- Model predictions showed good agreement with hospital air-sampling datasets, with the 50-percentile of saliva mass providing the closest match.
Conclusions:
- The developed framework provides a more accurate method for quantifying airborne viral RNA exposure.
- The model can serve as a pre-processor for infection risk assessment and a decision-making support tool for public health.
- An online web tool is available for users to analyze scenario-specific outcomes by adjusting input parameters.
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