Acceptance of a computer vision facilitated protocol to measure adherence to face mask use: a single-site, observational cohort study among hospital staff.

OBJECTIVES: Mask adherence continues to be a critical public health measure to prevent transmission of aerosol pathogens, such as SARS-CoV-2. We aimed to develop and deploy a computer vision algorithm to provide real-time feedback of mask wearing among staff in a hospital. DESIGN: Single-site, observational cohort study. SETTING: An urban, academic hospital in Boston, Massachusetts, USA. PARTICIPANTS: We enrolled adult hospital staff entering the hospital at a key ingress point. INTERVENTIONS: Consenting participants entering the hospital were invited to experience the computer vision mask detection system. Key aspects of the detection algorithm and feedback were described to participants, who then completed a quantitative assessment to understand their perceptions and acceptance of interacting with the system to detect their mask adherence. OUTCOME MEASURES: Primary outcomes were willingness to interact with the mask system, and the degree of comfort participants felt in interacting with a public facing computer vision mask algorithm. RESULTS: One hundred and eleven participants with mean age 40 (SD15.5) were enrolled in the study. Males (47.7%) and females (52.3%) were equally represented, and the majority identified as white (N=54, 49%). Most participants (N=97, 87.3%) reported acceptance of the system and most participants (N=84, 75.7%) were accepting of deployment of the system to reinforce mask adherence in public places. One third of participants (N=36) felt that a public facing computer vision system would be an intrusion into personal privacy.Public-facing computer vision software to detect and provide feedback around mask adherence may be acceptable in the hospital setting. Similar systems may be considered for deployment in locations where mask adherence is important.

Formative acceptance of ingestible biosensors to measure adherence to TB medications.

BACKGROUND: Tuberculosis (TB) represents a significant public health threat in India. Adherence to antitubercular therapy (ATT) is the key to reducing the burden of this infectious disease. Suboptimal adherence to ATT and lack of demonstrated feasibility of current strategies for monitoring ATT adherence highlights the need for alternative adherence monitoring systems. METHODS: A quantitative survey was conducted to assess the acceptance of and willingness to use a digital pill system (DPS) as a tool for monitoring ATT adherence among stakeholders directly involved in the management of patients with TB in India. Participants reviewed a video explaining the DPS and completed a survey, which covered sociodemographics, degree of involvement with TB patients, initial impressions of the DPS, and perceived challenges for deploying the technology in India. Participants were also asked to interpret mock DPS adherence data. RESULTS: The mean age was 34.3 (SD = 7.3), and participants (N = 50) were predominantly male (70%). The sample comprised internists (52%) and pulmonologists (30%), with a median of 4 years' experience (IQR 3, 6) in the management of TB patients. No participants had previously used a DPS, but some reported prior awareness of the technology (22%). Most reported that they would recommend use of a DPS to patients on ATT (76%), and that they would use a DPS in both the intensive and continuation phases of TB management (64%). The majority viewed the DPS (82%) as a useful alternative to directly observed therapy-short course (DOTS), particularly given the ongoing COVID-19 pandemic. Participants reported that a DPS would be most effective in patients at risk of nonadherence (64%), as well as those with past nonadherence (64%). Perceived barriers to DPS implementation included lack of patient willingness (92%), cost (86%), and infrastructure constraints (66%). The majority of participants were able to accurately interpret patterns of adherence (80%), suboptimal adherence (90%), and frank nonadherence (82%) when provided with mock DPS data. CONCLUSIONS: DPS are viewed as an acceptable, feasible, and useful technology for monitoring ATT adherence by stakeholders directly involved in TB management. Future investigations should explore patient acceptance of DPS and pilot demonstration of the system in the TB context.

Mobile Robotic Platform for Contactless Vital Sign Monitoring.

The COVID-19 pandemic has accelerated methods to facilitate contactless evaluation of patients in hospital settings. By minimizing in-person contact with individuals who may have COVID-19, healthcare workers can prevent disease transmission and conserve personal protective equipment. Obtaining vital signs is a ubiquitous task that is commonly done in person by healthcare workers. To eliminate the need for in-person contact for vital sign measurement in the hospital setting, we developed Dr. Spot, a mobile quadruped robotic system. The system includes IR and RGB cameras for vital sign monitoring and a tablet computer for face-to-face medical interviewing. Dr. Spot is teleoperated by trained clinical staff to simultaneously measure the skin temperature, respiratory rate, and heart rate while maintaining social distancing from patients and without removing their mask. To enable accurate, contactless measurements on a mobile system without a static black body as reference, we propose novel methods for skin temperature compensation and respiratory rate measurement at various distances between the subject and the cameras, up to 5 m. Without compensation, the skin temperature MAE is 1.3°C. Using the proposed compensation method, the skin temperature MAE is reduced to 0.3°C. The respiratory rate method can provide continuous monitoring with a MAE of 1.6 BPM in 30 s or rapid screening with a MAE of 2.1 BPM in 10 s. For the heart rate estimation, our system is able to achieve a MAE less than 8 BPM in 10 s measured in arbitrary indoor light conditions at any distance below 2 m.

Metrics to relate COVID-19 wastewater data to clinical testing dynamics.

Wastewater surveillance has emerged as a useful tool in the public health response to the COVID-19 pandemic. While wastewater surveillance has been applied at various scales to monitor population-level COVID-19 dynamics, there is a need for quantitative metrics to interpret wastewater data in the context of public health trends. 24-hour composite wastewater samples were collected from March 2020 through May 2021 from a Massachusetts wastewater treatment plant and SARS-CoV-2 RNA concentrations were measured using RT-qPCR. The relationship between wastewater copy numbers of SARS-CoV-2 gene fragments and COVID-19 clinical cases and deaths varies over time. We demonstrate the utility of three new metrics to monitor changes in COVID-19 epidemiology: (1) the ratio between wastewater copy numbers of SARS-CoV-2 gene fragments and clinical cases (WC ratio), (2) the time lag between wastewater and clinical reporting, and (3) a transfer function between the wastewater and clinical case curves. The WC ratio increases after key events, providing insight into the balance between disease spread and public health response. Time lag and transfer function analysis showed that wastewater data preceded clinically reported cases in the first wave of the pandemic but did not serve as a leading indicator in the second wave, likely due to increased testing capacity, which allows for more timely case detection and reporting. These three metrics could help further integrate wastewater surveillance into the public health response to the COVID-19 pandemic and future pandemics.

Wastewater network infrastructure in public health: Applications and learnings from the COVID-19 pandemic.

Accurate estimates of COVID-19 burden of infections in communities can inform public health strategy for the current pandemic. Wastewater based epidemiology (WBE) leverages sewer infrastructure to provide insights on rates of infection by measuring viral concentrations in wastewater. By accessing the sewer network at various junctures, important insights regarding COVID-19 disease activity can be gained. The analysis of sewage at the wastewater treatment plant level enables population-level surveillance of disease trends and virus mutations. At the neighborhood level, WBE can be used to describe trends in infection rates in the community thereby facilitating local efforts at targeted disease mitigation. Finally, at the building level, WBE can suggest the presence of infections and prompt individual testing. In this critical review, we describe the types of data that can be obtained through varying levels of WBE analysis, concrete plans for implementation, and public health actions that can be taken based on WBE surveillance data of infectious diseases, using recent and successful applications of WBE during the COVID-19 pandemic for illustration.

Heal the Healers: A pilot study evaluating the feasibility, acceptability, and exploratory efficacy of a Transcendental Meditation intervention for emergency clinicians during the coronavirus disease 2019 pandemic.

OBJECTIVE: Emergency clinicians face elevated rates of burnout that result in poor outcomes for clinicians, patients, and health systems. The objective of this single-arm pilot study was to evaluate the feasibility of a Transcendental Meditation (TM) intervention for emergency clinicians during the coronavirus disease 2019 (COVID-19) pandemic and to explore the potential effectiveness in improving burnout, sleep, and psychological health. METHODS: Emergency clinicians (physicians, nurses, and physician-assistants) from 2 urban hospitals were recruited to participate in TM instruction (8 individual or group in-person and remote sessions) for 3 months. Session attendance was the primary feasibility outcome (prespecified as attending 6/8 sessions), and burnout was the primary clinical outcome. Participant-reported measures of feasibility and validated measures of burnout, depression, anxiety, sleep disturbance, and stress were collected at baseline and the 1-month and 3-month follow-ups. Descriptive statistics and linear mixed-effects models were used. RESULTS: Of the 14 physicians (46%), 7 nurses (22%), and 10 physician-assistants (32%) who participated, 61% were female (n = 19/32). TM training and at-home meditation practice was feasible for clinicians as 90.6% (n = 29/32) attended 6/8 training sessions and 80.6% self-reported meditating at least once a day on average. Participants demonstrated significant reductions in burnout (P < .05; effect sizes, Cohen's d = 0.43-0.45) and in symptoms of depression, anxiety, stress, and sleep disturbance (P values < .001; Cohen's d = 0.70-0.87). CONCLUSION: TM training was feasible for emergency clinicians during the COVID-19 pandemic and led to significant reductions in burnout and psychological symptoms. TM is a safe and effective meditation tool to improve clinicians' well-being.

Patient and Health Care Worker Perceptions of Communication and Ability to Identify Emotion When Wearing Standard and Transparent Masks.

Importance: Adoption of mask wearing in response to the COVID-19 pandemic alters daily communication. Objective: To assess communication barriers associated with mask wearing in patient-clinician interactions and individuals who are deaf and hard of hearing. Design, Setting, and Participants: This pilot cross-sectional survey study included the general population, health care workers, and health care workers who are deaf or hard of hearing in the United States. Volunteers were sampled via an opt-in survey panel and nonrandomized convenience sampling. The general population survey was conducted between January 5 and January 8, 2021. The health care worker surveys were conducted between December 3, 2020, and January 3, 2021. Respondents viewed 2 short videos of a study author wearing both a standard and transparent N95 mask and answered questions regarding mask use, communication, preference, and fit. Surveys took 15 to 20 minutes to complete. Main Outcomes and Measures: Participants' perceptions were assessed surrounding the use of both mask types related to communication and the ability to express emotions. Results: The national survey consisted of 1000 participants (mean [SD] age, 48.7 [18.5] years; 496 [49.6%] women) with a response rate of 92.25%. The survey of general health care workers consisted of 123 participants (mean [SD] age, 49.5 [9.0] years; 84 [68.3%] women), with a response rate of 11.14%. The survey of health care workers who are deaf or hard of hearing consisted of 45 participants (mean [SD] age, 54.5 [9.0] years; 30 [66.7%] women) with a response rate of 23.95%. After viewing a video demonstrating a study author wearing a transparent N95 mask, 781 (78.1%) in the general population, 109 general health care workers (88.6%), and 38 health care workers who are deaf or hard of hearing (84.4%) were able to identify the emotion being expressed, in contrast with 201 (20.1%), 25 (20.5%), and 11 (24.4%) for the standard opaque N95 mask. In the general population, 450 (45.0%) felt positively about interacting with a health care worker wearing a transparent mask; 76 general health care workers (61.8%) and 37 health care workers who are deaf or hard of hearing (82.2%) felt positively about wearing a transparent mask to communicate with patients. Conclusions and Relevance: The findings of this study suggest that transparent masks could help improve communication during the COVID-19 pandemic, particularly for individuals who are deaf and hard of hearing.

SARS-CoV-2 RNA concentrations in wastewater foreshadow dynamics and clinical presentation of new COVID-19 cases.

Current estimates of COVID-19 prevalence are largely based on symptomatic, clinically diagnosed cases. The existence of a large number of undiagnosed infections hampers population-wide investigation of viral circulation. Here, we quantify the SARS-CoV-2 concentration and track its dynamics in wastewater at a major urban wastewater treatment facility in Massachusetts, between early January and May 2020. SARS-CoV-2 was first detected in wastewater on March 3. SARS-CoV-2 RNA concentrations in wastewater correlated with clinically diagnosed new COVID-19 cases, with the trends appearing 4-10 days earlier in wastewater than in clinical data. We inferred viral shedding dynamics by modeling wastewater viral load as a convolution of back-dated new clinical cases with the average population-level viral shedding function. The inferred viral shedding function showed an early peak, likely before symptom onset and clinical diagnosis, consistent with emerging clinical and experimental evidence. This finding suggests that SARS-CoV-2 concentrations in wastewater may be primarily driven by viral shedding early in infection. This work shows that longitudinal wastewater analysis can be used to identify trends in disease transmission in advance of clinical case reporting, and infer early viral shedding dynamics for newly infected individuals, which are difficult to capture in clinical investigations.

"Waste Not, Want Not" - Leveraging Sewer Systems and Wastewater-Based Epidemiology for Drug Use Trends and Pharmaceutical Monitoring.

During the current global COVID-19 pandemic and opioid epidemic, wastewater-based epidemiology (WBE) has emerged as a powerful tool for monitoring public health trends by analysis of biomarkers including drugs, chemicals, and pathogens. Wastewater surveillance downstream at wastewater treatment plants provides large-scale population and regional-scale aggregation while upstream surveillance monitors locations at the neighborhood level with more precise geographic analysis. WBE can provide insights into dynamic drug consumption trends as well as environmental and toxicological contaminants. Applications of WBE include monitoring policy changes with cannabinoid legalization, tracking emerging illicit drugs, and early warning systems for potent fentanyl analogues along with the resurging wave of stimulants (e.g., methamphetamine, cocaine). Beyond drug consumption, WBE can also be used to monitor pharmaceuticals and their metabolites, including antidepressants and antipsychotics. In this manuscript, we describe the basic tenets and techniques of WBE, review its current application among drugs of abuse, and propose methods to scale and develop both monitoring and early warning systems with respect to measurement of illicit drugs and pharmaceuticals. We propose new frontiers in toxicological research with wastewater surveillance including assessment of medication assisted treatment of opioid use disorder (e.g., buprenorphine, methadone) in the context of other social burdens like COVID-19 disease.

Thinking green: modelling respirator reuse strategies to reduce cost and waste.

OBJECTIVES: To compare the impact of respirator extended use and reuse strategies with regard to cost and sustainability during the COVID-19 pandemic. DESIGN: Cost analysis. SETTING: USA. PARTICIPANTS: All healthcare workers within the USA. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: A model was developed to estimate usage, costs and waste incurred by several respirator usage strategies over the first 6 months of the pandemic in the USA. This model assumed universal masking of all healthcare workers. Estimates were taken from the literature, government databases and commercially available data from approved vendors. RESULTS: A new N95 respirator per patient encounter would require 7.41 billion respirators, cost $6.38 billion and generate 84.0 million kg of waste in the USA over 6 months. One respirator per day per healthcare worker would require 3.29 billion respirators, cost $2.83 billion and generate 37.22 million kg of waste. Decontamination by ultraviolet germicidal irradiation would require 1.64 billion respirators, cost $1.41 billion and accumulate 18.61 million kg of waste. H2O2 vapour decontamination would require 1.15 billion respirators, cost $1.65 billion and produce 13.03 million kg of waste. One reusable respirator with daily disposable filters would require 18 million respirators, cost $1.24 billion and generate 15.73 million kg of waste. Pairing a reusable respirator with H2O2 vapour-decontaminated filters would reduce cost to $831 million and generate 1.58 million kg of waste. The use of one surgical mask per healthcare worker per day would require 3.29 billion masks, cost $460 million and generate 27.92 million kg of waste. CONCLUSIONS: Decontamination and reusable respirator-based strategies decreased the number of respirators used, costs and waste generated compared with single-use or daily extended-use of disposable respirators. Future development of low-cost,simple technologies to enable respirator and/or filter decontamination is needed to further minimise the economic and environmental costs of masks.

Wastewater surveillance of SARS-CoV-2 across 40 U.S. states from February to June 2020.

Wastewater-based disease surveillance is a promising approach for monitoring community outbreaks. Here we describe a nationwide campaign to monitor SARS-CoV-2 in the wastewater of 159 counties in 40 U.S. states, covering 13% of the U.S. population from February 18 to June 2, 2020. Out of 1,751 total samples analyzed, 846 samples were positive for SARS-CoV-2 RNA, with overall viral concentrations declining from April to May. Wastewater viral titers were consistent with, and appeared to precede, clinical COVID-19 surveillance indicators, including daily new cases. Wastewater surveillance had a high detection rate (>80%) of SARS-CoV-2 when the daily incidence exceeded 13 per 100,000 people. Detection rates were positively associated with wastewater treatment plant catchment size. To our knowledge, this work represents the largest-scale wastewater-based SARS-CoV-2 monitoring campaign to date, encompassing a wide diversity of wastewater treatment facilities and geographic locations. Our findings demonstrate that a national wastewater-based approach to disease surveillance may be feasible and effective.

Assessment of the Acceptability and Feasibility of Using Mobile Robotic Systems for Patient Evaluation.

Importance: Before the widespread implementation of robotic systems to provide patient care during the COVID-19 pandemic occurs, it is important to understand the acceptability of these systems among patients and the economic consequences associated with the adoption of robotics in health care settings. Objective: To assess the acceptability and feasibility of using a mobile robotic system to facilitate health care tasks. Design, Setting, and Participants: This study included 2 components: a national survey to examine the acceptability of using robotic systems to perform health care tasks in a hospital setting and a single-site cohort study of patient experiences and satisfaction with the use of a mobile robotic system to facilitate triage and telehealth tasks in the emergency department (ED). The national survey comprised individuals living in the US who participated in a sampling-based survey via an online analytic platform. Participants completed the national survey between August 18 and August 21, 2020. The single-site cohort study included patients living in the US who presented to the ED of a large urban academic hospital providing quaternary care in Boston, Massachusetts between April and August 2020. All data were analyzed from August to October 2020. Exposures: Participants in the national survey completed an online survey to measure the acceptability of using a mobile robotic system to perform health care tasks (facilitating telehealth interviews, acquiring vital signs, obtaining nasal or oral swabs, placing an intravenous catheter, performing phlebotomy, and turning a patient in bed) in a hospital setting in the contexts of general interaction and interaction during the COVID-19 pandemic. Patients in the cohort study were exposed to a mobile robotic system, which was controlled by an ED clinician and used to facilitate a triage interview. After exposure, patients completed an assessment to measure their satisfaction with the robotic system. Main Outcomes and Measures: Acceptability of the use of a mobile robotic system to facilitate health care tasks in a hospital setting (national survey) and feasibility and patient satisfaction regarding the use of a mobile robotic system in the ED (cohort study). Results: For the national survey, 1154 participants completed all acceptability questions, representing a participation rate of 35%. After sample matching, a nationally representative sample of 1000 participants (mean [SD] age, 48.7 [17.0] years; 535 women [53.5%]) was included in the analysis. With regard to the usefulness of a robotic system to perform specific health care tasks, the response of "somewhat useful" was selected by 373 participants (37.3%) for facilitating telehealth interviews, 350 participants (35.0%) for acquiring vital signs, 307 participants (30.7%) for obtaining nasal or oral swabs, 228 participants (22.8%) for placing an intravenous catheter, 249 participants (24.9%) for performing phlebotomy, and 371 participants (37.1%) for turning a patient in bed. The response of "extremely useful" was selected by 287 participants (28.7%) for facilitating telehealth interviews, 413 participants (41.3%) for acquiring vital signs, 192 participants (19.2%) for obtaining nasal or oral swabs, 159 participants (15.9%) for placing an intravenous catheter, 167 participants (16.7%) for performing phlebotomy, and 371 participants (37.1%) for turning a patient in bed. In the context of the COVID-19 pandemic, the median number of individuals who perceived the application of robotic systems to be acceptable for completing telehealth interviews, obtaining nasal and oral swabs, placing an intravenous catheter, and performing phlebotomy increased. For the ED cohort study, 51 individuals were invited to participate, and 41 participants (80.4%) enrolled. One participant was unable to complete the study procedures because of a signaling malfunction in the robotic system. Forty patients (mean [SD] age, 45.8 [2.7] years; 29 women [72.5%]) completed the mobile robotic system-facilitated triage interview, and 37 patients (92.5%) reported that the interaction was satisfactory. A total of 33 participants (82.5%) reported that their experience of receiving an interview facilitated by a mobile robotic system was as satisfactory as receiving an in-person interview from a clinician. Conclusions and Relevance: In this study, a mobile robotic system was perceived to be acceptable for use in a broad set of health care tasks among survey respondents across the US. The use of a mobile robotic system enabled the facilitation of contactless triage interviews of patients in the ED and was considered acceptable among participants. Most patients in the ED rated the quality of mobile robotic system-facilitated interaction to be equivalent to in-person interaction with a clinician.

Prospective Evaluation of the Transparent, Elastomeric, Adaptable, Long-Lasting (TEAL) Respirator.

N95 filtering facepiece respirators (FFR) and surgical masks are essential in reducing airborne disease transmission, particularly during the COVID-19 pandemic. However, currently available FFR's and masks have major limitations, including masking facial features, waste, and integrity after decontamination. In a multi-institutional trial, we evaluated a transparent, elastomeric, adaptable, long-lasting (TEAL) respirator to evaluate success of qualitative fit test with user experience and biometric evaluation of temperature, respiratory rate, and fit of respirator using a novel sensor. There was a 100% successful fit test among participants, with feedback demonstrating excellent or good fit (90% of participants), breathability (77.5%), and filter exchange (95%). Biometric testing demonstrated significant differences between exhalation and inhalation pressures among a poorly fitting respirator, well-fitting respirator, and the occlusion of one filter of the respirator. We have designed and evaluated a transparent elastomeric respirator and a novel biometric feedback system that could be implemented in the hospital setting.

Regulatory, safety, and privacy concerns of home monitoring technologies during COVID-19.

There has been increasing interest in the use of home monitoring technologies during the COVID-19 pandemic to decrease interpersonal contacts and the resultant risks of exposure for people to the coronavirus SARS-CoV-2. This Perspective explores how the accelerated development of these technologies also raises major concerns pertaining to safety and privacy. We make recommendations for needed interventions to ensure safety and review best practices and US regulatory requirements for privacy and security. We discuss, among other topics, Emergency Use Authorizations for medical devices and privacy laws of the USA and Europe.

SARS-CoV-2 Titers in Wastewater Are Higher than Expected from Clinically Confirmed Cases.

Wastewater surveillance represents a complementary approach to clinical surveillance to measure the presence and prevalence of emerging infectious diseases like the novel coronavirus SARS-CoV-2. This innovative data source can improve the precision of epidemiological modeling to understand the penetrance of SARS-CoV-2 in specific vulnerable communities. Here, we tested wastewater collected at a major urban treatment facility in Massachusetts and detected SARS-CoV-2 RNA from the N gene at significant titers (57 to 303 copies per ml of sewage) in the period from 18 to 25 March 2020 using RT-qPCR. We validated detection of SARS-CoV-2 by Sanger sequencing the PCR product from the S gene. Viral titers observed were significantly higher than expected based on clinically confirmed cases in Massachusetts as of 25 March. Our approach is scalable and may be useful in modeling the SARS-CoV-2 pandemic and future outbreaks.IMPORTANCE Wastewater-based surveillance is a promising approach for proactive outbreak monitoring. SARS-CoV-2 is shed in stool early in the clinical course and infects a large asymptomatic population, making it an ideal target for wastewater-based monitoring. In this study, we develop a laboratory protocol to quantify viral titers in raw sewage via qPCR analysis and validate results with sequencing analysis. Our results suggest that the number of positive cases estimated from wastewater viral titers is orders of magnitude greater than the number of confirmed clinical cases and therefore may significantly impact efforts to understand the case fatality rate and progression of disease. These data may help inform decisions surrounding the advancement or scale-back of social distancing and quarantine efforts based on dynamic wastewater catchment-level estimations of prevalence.

Injection Molded Autoclavable, Scalable, Conformable (iMASC) system for aerosol-based protection: a prospective single-arm feasibility study.

OBJECTIVE: To develop and test a new reusable, sterilisable N95 filtering facepiece respirator (FFR)-comparable face mask, known as the Injection Molded Autoclavable, Scalable, Conformable (iMASC) system, given the dire need for personal protective equipment within healthcare settings during the COVID-19 pandemic. DESIGN: Single-arm feasibility study. SETTING: Emergency department and outpatient oncology clinic. PARTICIPANTS: Healthcare workers who have previously undergone N95 fit testing. INTERVENTIONS: Fit testing of new iMASC system. PRIMARY AND SECONDARY OUTCOME MEASURES: Primary outcome is success of fit testing using an Occupational Safety and Health Administration (OSHA)-approved testing method, and secondary outcomes are user experience with fit, breathability and filter replacement. RESULTS: Twenty-four subjects were recruited to undergo fit testing, and the average age of subjects was 41 years (range of 21-65 years) with an average body mass index of 26.5 kg/m2. The breakdown of participants by profession was 46% nurses (n=11), 21% attending physicians (n=5), 21% resident physicians (n=5) and 12% technicians (n=3). Of these participants, four did not perform the fit testing due to the inability to detect saccharin solution on premask placement sensitivity test, lack of time and inability to place mask over hair. All participants (n=20) who performed the fit test were successfully fitted for the iMASC system using an OSHA-approved testing method. User experience with the iMASC system, as evaluated using a Likert scale with a score of 1 indicating excellent and a score of 5 indicating very poor, demonstrated an average fit score of 1.75, breathability of 1.6, and ease of replacing the filter on the mask was scored on average as 2.05. CONCLUSIONS: The iMASC system was shown to successfully fit multiple different face sizes and shapes using an OSHA-approved testing method. These data support further certification testing needed for use in the healthcare setting.

Intentional Hydroxychloroquine Overdose Treated with High-Dose Diazepam: an Increasing Concern in the COVID-19 Pandemic.

INTRODUCTION: Recent attention on the possible use of hydroxychloroquine and chloroquine to treat COVID-19 disease has potentially triggered a number of overdoses from hydroxychloroquine. Toxicity from hydroxychloroquine manifests with cardiac conduction abnormalities, seizure activity, and muscle weakness. Recognizing this toxidrome and unique management of this toxicity is important in the COVID-19 pandemic. CASE REPORT: A 27-year-old man with a history of rheumatoid arthritis presented to the emergency department 7 hours after an intentional overdose of hydroxychloroquine. Initial presentation demonstrated proximal muscle weakness. The patient was found to have a QRS complex of 134 ms and QTc of 710 ms. He was treated with early orotracheal intubation and intravenous diazepam boluses. Due to difficulties formulating continuous diazepam infusions, we opted to utilize an intermitted intravenous bolus strategy that achieved similar effects that a continuous infusion would. The patient recovered without residual side effects. DISCUSSION: Hydroxychloroquine toxicity is rare but projected to increase in frequency given its selection as a potential modality to treat COVID-19 disease. It is important for clinicians to recognize the unique effects of hydroxychloroquine poisoning and initiate appropriate emergency maneuvers to improve the outcomes in these patients.