Due to the COVID-19 pandemic, current high demand for N95 filtering facepiece respirators has placed them in short supply. Filtering facepiece respirator wearers have traditionally been instructed to discard their respirator and don a new one should the respirator become saturated with perspiration or damp from exhaled breath. However, today’s shortage may prohibit many N95 respirator wearers from replacing their filtering facepieces at this desired frequency. Previously unpublished research that evaluated the performance of N95 filtering facepiece respirators saturated with artificial perspiration and then dried out can help provide insight into making critical decisions about the change out frequency of N95 respirators that become damp with use. This study concluded that the collection efficiency of filtering facepiece respirators, containing electrostatic filter media, remained statistically unchanged or slightly improved after being dried out following harsh saturation conditions with artificial perspiration. Therefore, respirator wearers can continue to rely on their N95 filtering facepiece respirators to perform as intended.

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This study presents a quantitative validation of 15 Similar Exposure Groups (SEGs) that were derived via control bands inherent to the Risk Level Based Management System currently being used at the Lawrence Livermore National Laboratory. For 93% of the SEGs that were evaluated, statistical analyses of personal exposure monitoring data, through Bayesian Decision Analysis (BDA), demonstrated that the controls implemented from the initial control bands assigned to these SEGs were at least as protective as the controls from the control band outcomes derived from the quantitative data. The BDA also demonstrated that for 40% of the SEGs, the controls from the initial control bands were overly protective, thus allowing controls to be downgraded, which resulted in a significant saving of environmental safety and health (ES&H) resources. Therefore, as a means to both confirm existing controls and to identify candidate SEGs for downgrading controls, efforts to continuously improve the accuracy of Control Banding (CB) strategies through the routine quantitative validation of SEGs are strongly encouraged. Targeted collaborative efforts across institutions and even countries for both the development of CB strategies and the validation of discreetly defined SEGs of commonly performed tasks will not only optimize limited ES&H resources but will also assist in providing a simplified process for essential risk communication at the worker level to the benefit of billions of workers around the world.