German Social Accident Insurance Institution for the Health and Welfare Services (BGW), Department for Occupational Medicine, Hazardous Substances and Public Health, Pappelallee 33/35/37, 22089, Hamburg, Germany.
Federal Institute for Occupational Safety and Health (BAuA), Unit Exposure Assessment Biocides, Friedrich-Henkel-Weg 1-25, 44149, Dortmund, Germany.
J Expo Sci Environ Epidemiol. 2024 Mar;34(2):345-355. doi: 10.1038/s41370-023-00633-y. Epub 2023 Dec 25.
For healthcare workers, surface disinfections are daily routine tasks. An assessment of the inhalation exposure to hazardous substances, in this case the disinfectant´s active ingredients, is necessary to ensure workers safety. However, deciding which exposure model is best for exposure assessment remains difficult.
The aim of the study was to evaluate the applicability of different exposure models for disinfection of small surfaces in healthcare settings.
Measurements of the air concentration of active ingredients in disinfectants (ethanol, formaldehyde, glutaraldehyde, hydrogen peroxide, peroxyacetic acid) together with other exposure parameters were recorded in a test chamber. The measurements were performed using personal and stationary air sampling. In addition, exposure modelling was performed using three deterministic models (unsteady 1-zone, ConsExpo and 2-component) and one modifying-factor model (Stoffenmanager®). Their estimates were compared with the measured values using various methods to assess model quality (like accuracy and level of conservatism).
The deterministic models showed overestimation predominantly in the range of two- to fivefold relative to the measured data and high conservatism for all active ingredients of disinfectants with the exception of ethanol. With Stoffenmanager® an exposure distribution was estimated for ethanol, which was in good accordance with the measured data.
To date, workplace exposure assessments often involve expensive and time consuming air measurements. Reliable exposure models can be used to assess occupational inhalation exposure to hazardous substances, in this case surface disinfectants. This study describes the applicability of three deterministic and one modifying-factor model for disinfection of small surfaces in healthcare settings, in direct comparison to measurements performed and will facilitate future exposure assessments at these workplaces.
对于医护人员来说，表面消毒是日常例行任务。为了确保工作人员的安全，有必要评估接触有害物质的吸入暴露，在这种情况下，评估的是消毒剂的有效成分。然而，决定哪种暴露模型最适合暴露评估仍然很困难。
本研究的目的是评估不同暴露模型在医疗环境中小面积表面消毒中的适用性。
在测试室中测量消毒剂（乙醇、甲醛、戊二醛、过氧化氢、过氧乙酸）的活性成分的空气浓度以及其他暴露参数。使用个人和固定空气采样进行测量。此外，使用三种确定性模型（非稳态 1 区、ConsExpo 和 2 成分）和一种修正因子模型（Stoffenmanager®）进行暴露建模。使用各种方法（如准确性和保守程度）将模型估计值与测量值进行比较，以评估模型质量。
与测量数据相比，确定性模型主要表现出 2 到 5 倍的高估，并且对消毒剂的所有有效成分都具有高度的保守性，乙醇除外。对于乙醇，Stoffenmanager®估计了暴露分布，与测量数据非常吻合。
迄今为止，工作场所暴露评估通常涉及昂贵且耗时的空气测量。可靠的暴露模型可用于评估职业性吸入接触有害物质，在这种情况下是表面消毒剂。本研究描述了三种确定性模型和一种修正因子模型在医疗环境中小面积表面消毒中的适用性，直接与实际测量结果进行比较，并将为这些工作场所的未来暴露评估提供便利。
