Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, Arizona, USA
Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, Arizona, USA.
Appl Environ Microbiol. 2018 Aug 31;84(18). doi: 10.1128/AEM.00709-18. Print 2018 Sep 15.
Nosocomial viral infections are an important cause of health care-acquired infections where fomites have a role in transmission. Using stochastic modeling to quantify the effects 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 to determine needed viral reductions to achieve risk targets. Rotavirus, rhinovirus, and influenza A virus infection risks for two cases were modeled. Case 1 utilized a single fomite contact approach, while case 2 assumed 6 h of contact activities. A 94.1% viral reduction on surfaces and hands was measured following a single cleaning round using an Environmental Protection Agency (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 median viral infection risks being reduced by 92.96 to 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 the manufacturer's instructions. However, there are currently no standards for health care 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 health care 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 health care worker behaviors, and infection risks.
医院病毒性感染是医院获得性感染的一个重要原因，其中接触传播是病原体传播的一种方式。使用随机模型来量化表面消毒措施对医院病原体暴露和感染风险的影响，可以为清洁实践提供信息。本研究的目的是预测表面消毒对病毒感染风险的影响，并确定实现风险目标所需的病毒减少量。模拟了两种情况下的轮状病毒、鼻病毒和甲型流感病毒感染风险。案例 1 采用单次接触病原体的方法，而案例 2 假设接触活动持续 6 小时。在一家紧急护理机构中，使用美国环保署（EPA）注册的消毒剂进行单次清洁后，表面和手上的病毒减少率为 94.1%。该值用于模拟表面消毒干预对感染风险的影响。还模拟了其他表面清洁效果的风险降低。估计了实现风险概率目标所需的表面减少量。在案例 1 条件下，病毒表面浓度减少 94.1%，感染风险降低 94.1%。在案例 2 条件下，表面减少 94.1%，导致中位数病毒感染风险降低 92.96%至 94.1%，甲型流感病毒感染风险降低至一百万分之一以下。方程中的表面浓度与剂量和感染风险输出高度相关。对于轮状病毒和鼻病毒，需要将病毒表面减少>99.99%，才能达到百万分之一的风险目标。本研究量化了与表面消毒剂使用相关的感染风险降低，并表明对于低感染剂量的生物体，实现风险目标可能更具挑战性。已知如果按照制造商的说明使用美国环保署注册的表面消毒剂喷雾，可以降低感染风险。然而，目前在医疗保健环境中，还没有与表面污染水平相关的标准。本研究的意义在于，使用医疗保健环境中实际的表面病毒浓度来量化实现各种风险目标所需的减少量。该研究通过演示需要多次应用才能降低风险，并强调需要更多模型来探索表面微生物污染、患者和医护人员行为以及感染风险之间的关系，为清洁方案的设计提供了信息。
