Fomite disinfection using spray systems: A computational multi-physics framework.

Area of Science:

• Multiphysics modeling
• Computational fluid dynamics
• Infectious disease control

Background:

• Spray disinfection of fomites (inanimate objects carrying pathogens) is crucial for reducing healthcare-associated and community-acquired infections.
• Predicting the effectiveness of spray disinfection systems is complex due to multi-physics phenomena and numerous parameters.
• Non-porous hydrophilic surfaces present unique challenges for disinfectant droplet interaction and pathogen inactivation.

Purpose of the Study:

• To develop and validate a computational multi-physics framework for evaluating spray disinfection systems.
• To assess the performance and effectiveness of these systems on fomites with non-porous hydrophilic surfaces.
• To provide a predictive tool for optimizing disinfection strategies and improving public health.

Main Methods:

• A multi-physics framework was developed, encompassing four key phases: droplet atomization, droplet-air interaction, droplet-surface impingement, and disinfectant-pathogen interaction.
• The framework models the complex dynamics of liquid disinfectant spray systems.
• Validation was performed using experimental data on the reduction of viable Bacillus atrophaeus spores over 1800 seconds.

Main Results:

• The computational framework accurately predicted fomite disinfection efficacy.
• Deviations between predicted and measured data were minimal, at 2.73% and 2.38%.
• The model successfully captured the dynamics of spray disinfection on non-porous hydrophilic surfaces.

Conclusions:

• The developed multi-physics framework provides a reliable method for predicting spray disinfection performance.
• This predictive capability can enhance public health practices by informing the design of more effective disinfection strategies.
• The framework offers potential for targeted disinfection in diverse settings, improving overall hygiene and safety.