Ultraviolet germicidal irradiation: A prediction model to estimate UV-C-induced infectivity loss in single-strand RNA viruses

Abstract

Ultraviolet germicidal irradiation (UVGI) disinfection technology is effective in inactivating microorganisms. However, its performance can vary against different microorganisms due to their diverse structural and genomic features. Thus, rapid predictions of UV (254 nm) inactivation kinetics are essential, particularly for highly infectious emerging pathogens, such as SARS-CoV-2, during the extemporary COVID-19 pandemic. In this study, aiming at single-strand RNA (ssRNA) viruses, an improved genomic model was introduced to predict the UV inactivation kinetics of viral genomes using genome sequence data. First, the overall virus infectivity loss in an aqueous matrix was estimated as the sum of damage to both the entire genome and the protein capsid. Then, the “UV rate constant ratio of aerosol and liquid” was used to convert the UV rate constant for viruses in a liquid-based matrix to an airborne state. The prediction model underwent both quantitative and qualitative validation using experimental data from this study and the literature. Finally, with the goal of mitigating potential airborne transmission of ssRNA viruses in indoor environments, this paper summarizes existing in-duct UVGI system designs and evaluates their germicidal performance. The prediction model may serve as a preliminary tool to assess the effectiveness of a UVGI system for emerging or unculturable viruses or to estimate the required UV dose when designing such a system.