Applying the CDC Science Impact Framework to the results of the National Institute for Occupational Safety and Health and the Bureau of Labor Statistics 2001 survey of respirator use and practices.

During 2001-2002, the National Institute for Occupational Safety and Health (NIOSH), at the United States Centers for Disease Control and Prevention, collaborated with the Bureau of Labor Statistics (BLS) at the United States Department of Labor to conduct a voluntary survey of U.S. employers regarding the use of respiratory protective devices. In 2003, the survey results were jointly published by NIOSH and BLS. This study highlights and evaluates the scientific impact of the 2001-2002 survey by using the Science Impact Framework which provides a historical tracking method with five domains of influence. The authors conducted interviews with original project management as well as a thorough document review and qualitative content analysis of published papers, books, presentations, and other relevant print media. A semi-structured and cross-vetted coding was applied across the five domains: Disseminating Science, Creating Awareness, Catalyzing Action, Effecting Change, and Shaping the Future. The 2001-2002 survey findings greatly enhanced understanding and awareness of respirator use in occupational settings within the United States. It also led to similar surveys in other countries, regulatory initiatives by the Occupational Safety and Health Administration and Mine Safety and Health Administration, and ultimately to a renewed partnership between NIOSH and BLS to collect contemporary estimates of respirator use in the workplace within the United States.

Respiratory Protection in a Time of Crisis: NIOSH Testing of International Respiratory Protective Devices for Emergency Use.

National Institute for Occupational Safety and Health (NIOSH)-approved respirators are required by the Occupational Safety and Health Administration (OSHA) when personal respiratory protection is used in US occupational settings. During the COVID-19 pandemic, the demand for NIOSH-approved N95 filtering facepiece respirators overwhelmed the available supply. To supplement the national inventory of N95 respirators, contingency and crisis capacity strategies were implemented and incorporated a component that endorsed the use of non-NIOSH-approved respiratory protective devices that conformed to select international standards. The development and execution of this strategy required the collaborative effort of numerous agencies. The Food and Drug Administration temporarily authorized non-NIOSH-approved international respiratory protective devices through an emergency use authorization, OSHA relaxed their enforcement guidance concerning their use in US workplaces, and NIOSH initiated a supplemental performance assessment process to verify the quality of international devices. NIOSH testing revealed that many of the non-NIOSH-approved respiratory protective devices had filtration efficiencies below 95% and substantial inconsistencies in filtration performance. This article reports the results of the NIOSH testing to date and discusses how it has contributed to continuous improvement of the crisis strategy of temporarily permitting the use of non-NIOSH-approved respirators in US occupational settings during the COVID-19 pandemic.

Elastomeric Half Mask Respirators: An Alternative to Disposable Respirators and a Solution to Shortages during Public Health Emergencies.

During public health emergencies such as an influenza pandemic, disposable filtering facepiece respirator (FFR) shortages have a significant impact on the national response, affecting many types of workplaces that rely on respiratory protection. During the COVID-19 pandemic, severe FFR shortages led the CDC to publish strategies for optimizing the supply of N95 FFRs. These strategies included the extended use and limited reuse of FFRs, wearing decontaminated FFRs, wearing respirators that meet an international respirator standard, or wearing FFRs that were past their manufacturer-designated shelf life. An additional strategy to mitigate supply shortages that was highlighted during the COVID-19 pandemic was to wear reusable respirators, such as elastomeric half mask respirators (EHMRs), or powered air-purifying respirators, which can be cleaned, disinfected, and reused. A decade of nationwide initiatives to increase the utility of EHMRs in healthcare settings were realized during the COVID-19 pandemic as EHMRs became more well-known and were used in healthcare settings for respiratory protection. This expanded use of EHMRs led to an increase in federal procurement, research, guidance, and private sector research and development of innovative EHMR designs by manufacturers to respond to workers' needs for both respiratory protection and source control. This paper describes the role of reusable EHMRs before and during the COVID-19 pandemic, and reviews past and current research, to inform successful EHMR implementation in healthcare and first responder settings.

Using Public Feedback about the use of Elastomeric Half Mask Respirators to Inform a National Deployment Study within Health Settings.

Reusable elastomeric half mask respirators (EHMRs) have been encouraged for use during conventional, contingency, and crisis capacity in healthcare delivery settings as an alternative to disposable N95 filtering facepiece respirators (FFRs). However, standard, operationalized guidelines for implementing EHMRs in healthcare and first responder settings are needed to facilitate such integration. Specifically, research is needed to identify and address specialized concerns in healthcare delivery settings beyond hospitals to understand the widespread barriers to EHMR use and how organizational culture can support or hinder EHMR adoption. The Strategic National Stockpile (SNS) requested support from the National Institute for Occupational Safety and Health (NIOSH) to develop its strategy to purchase and distribute EHMRs to interested health organizations. To support this SNS effort, NIOSH published a Federal Register Notice (FRN) to request formative input from the public on the nationwide distribution of EHMRs and provided the technical analysis of the responses. Twenty-two representatives from first responder organizations, healthcare and dental associations, manufacturers, higher education, medical/nursing societies, and a union provided comments for consideration. This feedback was qualitatively analyzed to identify themes among the comments. This paper discusses patterns that emerged in the feedback provided within the primary topics of perceived advantages and disadvantages of EHMRs and key considerations for a successful national deployment of EHMRs. This paper also discusses how the formative feedback received was critical to informing the SNS's strategy to purchase and deploy EHMRs for longitudinal demonstration projects with the goal to produce updated EHMR implementation guidelines and best practices.

Strategies for Optimizing the Supply of N95 Filtering Facepiece Respirators During the Coronavirus Disease 2019 (COVID-19) Pandemic.

N95 respirators are personal protective equipment most often used to control exposures to infections transmitted via the airborne route. Supplies of N95 respirators can become depleted during pandemics or when otherwise in high demand. In this paper, we offer strategies for optimizing supplies of N95 respirators in health care settings while maximizing the level of protection offered to health care personnel when there is limited supply in the United States during the 2019 coronavirus disease pandemic. The strategies are intended for use by professionals who manage respiratory protection programs, occupational health services, and infection prevention programs in health care facilities to protect health care personnel from job-related risks of exposure to infectious respiratory illnesses. Consultation with federal, state, and local public health officials is also important. We use the framework of surge capacity and the occupational health and safety hierarchy of controls approach to discuss specific engineering control, administrative control, and personal protective equipment measures that may help in optimizing N95 respirator supplies.

Personal Protective Equipment Supply Chain: Lessons Learned from Recent Public Health Emergency Responses.

Personal protective equipment (PPE) that protects healthcare workers from infection is a critical component of infection control strategies in healthcare settings. During a public health emergency response, protecting healthcare workers from infectious disease is essential, given that they provide clinical care to those who fall ill, have a high risk of exposure, and need to be assured of occupational safety. Like most goods in the United States, the PPE market supply is based on demand. The US PPE supply chain has minimal ability to rapidly surge production, resulting in challenges to meeting large unexpected increases in demand that might occur during a public health emergency. Additionally, a significant proportion of the supply chain is produced off-shore and might not be available to the US market during an emergency because of export restrictions or nationalization of manufacturing facilities. Efforts to increase supplies during previous public health emergencies have been challenging. During the 2009 H1N1 influenza pandemic and the 2014 Ebola virus epidemic, the commercial supply chain of pharmaceutical and healthcare products quickly became critical response components. This article reviews lessons learned from these responses from a PPE supply chain and systems perspective and examines ways to improve PPE readiness for future responses.

Evaluation of respiratory protection programs and practices in California hospitals during the 2009-2010 H1N1 influenza pandemic.

BACKGROUND: Emergence of the novel 2009 influenza A H1N1 virus in California led to an evaluation of hospital respiratory protection programs (RPPs) and practices by the California Department of Public Health during the 2009-2010 influenza season. METHODS: Onsite evaluation of 16 hospitals consisted of interviews with managers and health care workers about RPPs and practices, review of written RPPs, and limited observations of personnel using respirators. Data were analyzed using descriptive statistics. RESULTS: All hospitals had implemented policies requiring the minimum use of N95 filtering facepiece respirators when working with patients with H1N1 virus infection; 95.5% of health care workers (n = 199) reported they would wear at least this level of protection when in close contact with a patient with confirmed or suspected H1N1 virus infection. However, evaluation of written RPPs indicated deficiencies in required areas, most commonly in recordkeeping, designation of a program administrator, program evaluation, employee training, and fit testing procedures. CONCLUSIONS: Health care workers were aware of respiratory protection required when providing care for patients with confirmed or suspected H1N1 virus infection. Hospitals should improve written RPPs, fully implement written procedures, and conduct periodic program evaluation to ensure effectiveness of respirator use for health care worker protection. Increased accessibility of resources tailored for hospital respirator program administrators may be helpful.

A multi-feature and multi-channel univariate selection process for seizure prediction.

OBJECTIVE: To develop a prospective method for optimizing seizure prediction, given an array of implanted electrodes and a set of candidate quantitative features computed at each contact location. METHODS: The method employs a genetic-based selection process, and then tunes a probabilistic neural network classifier to predict seizures within a 10 min prediction horizon. Initial seizure and interictal data were used for training, and the remaining IEEG data were used for testing. The method continues to train and learn over time. RESULTS: Validation of these results over two workshop patients demonstrated a sensitivity of 100%, and 1.1 false positives per hour for Patient E, using a 2.4s block predictor, and a failure of the method on Patient B. CONCLUSIONS: This study demonstrates a prospective, exploratory implementation of a seizure prediction method designed to adapt to individual patients with a wide variety of pre-ictal patterns, implanted electrodes and seizure types. Its current performance is limited likely by the small number of input channels and quantitative features employed in this study, and segmentation of the data set into training and testing sets rather than using all continuous data available. SIGNIFICANCE: This technique theoretically has the potential to address the challenge presented by the heterogeneity of EEG patterns seen in medication-resistant epilepsy. A more comprehensive implementation utilizing all electrode sites, a broader feature library, and automated multi-feature fusion will be required to fully judge the method's potential for predicting seizures.

Continuous energy variation during the seizure cycle: towards an on-line accumulated energy.

OBJECTIVE: Increases in accumulated energy on intracranial EEG are associated with oncoming seizures in retrospective studies, supporting the idea that seizures are generated over time. Published seizure prediction methods require comparison to 'baseline' data, sleep staging, and selecting seizures that are not clustered closely in time. In this study, we attempt to remove these constraints by using a continuously adapting energy threshold, and to identify stereotyped energy variations through the seizure cycle (inter-, pre-, post- and ictal periods). METHODS: Accumulated energy was approximated by using moving averages of signal energy, computed for window lengths of 1 and 20 min, and an adaptive decision threshold. Predictions occurred when energy within the shorter running window exceeded the decision threshold. RESULTS: Predictions for time horizons of less than 3h did not achieve statistical significance in the data sets analyzed that had an average inter-seizure interval ranging from 2.9 to 8.6h. 51.6% of seizures across all patients exhibited stereotyped pre-ictal energy bursting and quiet periods. CONCLUSIONS: Accumulating energy alone is not sufficient for predicting seizures using a 20 min running baseline for comparison. Stereotyped energy patterns through the seizure cycle may provide clues to mechanisms underlying seizure generation. SIGNIFICANCE: Energy-based seizure prediction will require fusion of multiple complimentary features and perhaps longer running averages to compensate for post-ictal and sleep-induced energy changes.

Epileptic seizure prediction using hybrid feature selection over multiple intracranial EEG electrode contacts: a report of four patients.

Epileptic seizure prediction has steadily evolved from its conception in the 1970s, to proof-of-principle experiments in the late 1980s and 1990s, to its current place as an area of vigorous, clinical and laboratory investigation. As a step toward practical implementation of this technology in humans, we present an individualized method for selecting electroencephalogram (EEG) features and electrode locations for seizure prediction focused on precursors that occur within ten minutes of electrographic seizure onset. This method applies an intelligent genetic search process to EEG signals simultaneously collected from multiple intracranial electrode contacts and multiple quantitative features derived from these signals. The algorithm is trained on a series of baseline and preseizure records and then validated on other, previously unseen data using split sample validation techniques. The performance of this method is demonstrated on multiday recordings obtained from four patients implanted with intracranial electrodes during evaluation for epilepsy surgery. An average probability of prediction (or block sensitivity) of 62.5% was achieved in this group, with an average block false positive (FP) rate of 0.2775 FP predictions/h, corresponding to 90.47% specificity. These findings are presented as an example of a method for training, testing and validating a seizure prediction system on data from individual patients. Given the heterogeneity of epilepsy, it is likely that methods of this type will be required to configure intelligent devices for treating epilepsy to each individual's neurophysiology prior to clinical deployment.