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

Abstract

Disinfecting inanimate objects or materials carrying infectious agents, i.e., fomites, using spray systems reduces healthcare-associated infections in medical settings and community-acquired infections in non-medical environments. However, an accurate prediction of such systems is challenging as these systems embrace multi-physics phenomena depending on several parameters. Therefore, this paper presents a computational modeling-based multi-physics framework to evaluate the performance and effectiveness of spray systems employed in disinfecting fomites with non-porous hydrophilic surfaces. The framework includes four key phases: (i) atomizing the liquid disinfectant jet into the disinfectant droplets; (ii) interactions between disinfectant droplets and the surrounding air; (iii) impingements created by the disinfectant droplets on the fomite surface; (iv) interactions between the disinfectant depositions and pathogens causing fomite disinfection. The accuracy of the framework is evaluated using two sets of experimental data on the reduction of viable Bacillus atrophaeus spores over an 1800-second period. The results show that the framework can predict fomite disinfection via spray systems, with the deviations from the measured data being 2.73% and 2.38%. By presenting a detailed perception of the dynamics involved in fomite disinfection, this framework has the potential to improve public health practices and lead to the development of more effective and targeted disinfection strategies in diverse settings.

Keywords

• Public health
• Environmental health protection
• Biological contaminants
• Pathogenic microorganisms
• Infectious diseases
• COVID-19