Modelling surface disinfection needs to meet microbial risk reduction targets.

Nosocomial viral infections are an important cause of healthcare acquired infections where fomites have a role in transmission. Using stochastic modelling to quantify the effect of surface disinfection practices on nosocomial pathogen exposures and infection risk can inform cleaning practices. The purpose of this study was to predict the effect of surface disinfection on viral infection risks and determine needed viral reductions to achieve risk targets. Rotavirus, rhinovirus, and influenza A virus infection risks for two cases were modelled. Case 1 utilised a single fomite contact approach while Case 2 assumed six hours of contact activities. A 94.1% viral reduction on surfaces and hands was measured following a single cleaning round using of an EPA-registered disinfectant in an urgent care facility. This value was used to model the effect of a surface disinfection intervention on infection risk. Risk reductions for other surface cleaning efficacies were also simulated. Surface reductions required to achieve risk probability targets were estimated. Under Case 1 conditions, a 94.1% reduction in virus surface concentration reduced infection risks by 94.1%. Under Case 2 conditions, a 94.1% reduction on surfaces resulted in reduced median viral infection risks by 92.96 – 94.1% and an influenza A virus infection risk below one in a million. Surface concentration in the equations was highly correlated with dose and infection risk outputs. For rotavirus and rhinovirus, a >99.99% viral surface reduction would be needed to achieve a one in a million risk target. This study quantifies reductions of infection risk relative to surface disinfectant use and demonstrates that risk targets for low infectious dose organisms may be more challenging to achieve. It is known that the use of EPA-registered surface disinfectant sprays can reduce infection risk if used according to manufacturer instructions. However, there are currently no standards for healthcare environments related to contamination levels on surfaces. The significance of this research is in quantifying needed reductions to meet various risk targets using realistic viral concentrations on surfaces for healthcare environments. This research informs the design of cleaning protocols by demonstrating that multiple applications may be needed to reduce risk and by highlighting a need for more models exploring the relationship among microbial contamination of surfaces, patient and healthcare worker behaviours, and infection risks.

Authors: Wilson AM, Reynolds KA, Sexton JD, Canales RA. ; Full Source: Applied Environmental Microbiology. 2018 Jul 6. pii: AEM.00709-18. doi: 10.1128/AEM.00709-18. [Epub ahead of print]