Assessing virus infection probability in an office setting using stochastic simulation

Abstract

Viral infections are an occupational health concern for office workers and employers. The objectives of this study were to estimate rotavirus, rhinovirus, and influenza A virus infection risks in an office setting and quantify infection risk reductions for two hygiene interventions. In the first intervention, research staff used an ethanol-based spray disinfectant to clean high-touch non-porous surfaces in a shared office space. The second intervention included surface disinfection and also provided workers with alcohol-based hand sanitizer gel and hand sanitizing wipes to promote hand hygiene. Expected changes in surface concentrations due to these interventions were calculated. Human exposure and dose were simulated using a validated, steady-state model incorporated into a Monte Carlo framework. Stochastic inputs representing human behavior, pathogen transfer efficiency, and pathogen fate were utilized, in addition to a mixed distribution that accounted for surface concentrations above and below a limit of detection. Dose-response curves were then used to estimate infection risk. Estimates of percent risk reduction using mean values from baseline and surface disinfection simulations for rotavirus, rhinovirus, and influenza A infection risk were 14.5%, 16.1%, and 32.9%, respectively. For interventions with both surface disinfection and the promotion of personal hand hygiene, reductions based on mean values of infection risk were 58.9%, 60.8%, and 87.8%, respectively. This study demonstrated that surface disinfection and the use of personal hand hygiene products can help decrease virus infection risk in communal offices. Additionally, a variance-based sensitivity analysis revealed a greater relative importance of surface concentrations, assumptions of relevant exposure routes, and inputs representing human behavior in estimating risk reductions.