Novel Smart N95 Filtering Facepiece Respirator with Real-time Adaptive Fit Functionality and Wireless Humidity Monitoring for Enhanced Wearable Comfort (preprint)

The widespread emergence of the COVID-19 pandemic has transformed our lifestyle, and facial respirators have become an essential part of daily life. Nevertheless, the current respirators possess several limitations such as poor respirator fit because they are incapable of covering diverse human facial sizes and shapes, potentially diminishing the effect of wearing respirators. In addition, the current facial respirators do not inform the user of the air quality within the smart facepiece respirator in case of continuous long-term use. Here, we demonstrate the novel smart N-95 filtering facepiece respirator that incorporates the humidity sensor and pressure sensory feedback-enabled self-fit adjusting functionality for the effective performance of the facial respirator to prevent the transmission of airborne pathogens. The laser-induced graphene (LIG) constitutes the humidity sensor, and the pressure sensor array based on the dielectric elastomeric sponge monitors the respirator contact on the face of the user, providing the sensory information for a closed-loop feedback mechanism. As a result of the self-fit adjusting mode along with elastomeric lining, the fit factor is increased by 3.20 and 5 times at average and maximum respectively. We expect that the experimental proof-of-concept of this work will offer viable solutions to the current commercial respirators to address the limitations.

Effect of underlying comorbidities on the infection and severity of COVID-19 in South Korea (preprint)

ABSTRACT Background: The coronavirus disease (COVID-19) pandemic is an emerging threat worldwide. It is still unclear how comorbidities affect the risk of infection and severity of COVID-19. Methods: A nationwide retrospective case-control study of 65,149 individuals, aged 18 years or older, whose medical cost for COVID-19 testing were claimed until April 8, 2020. The diagnosis of COVID-19 and severity of COVID-19 infection were identified from the reimbursement data using diagnosis codes and based on whether respiratory support was used, respectively. Odds ratios were estimated using multiple logistic regression, after adjusting for age, sex, region, healthcare utilization, and insurance status. Results: The COVID-19 group (5,172 of 65,149) was younger and showed higher proportion of females. 5.6% (293 of 5,172) of COVID-19 cases were severe. The severe COVID-19 group had older patients and a higher male ratio than the non-severe group. Cushing syndrome (Odds ratio range (ORR) 2.059-2.358), chronic renal disease (ORR 1.292-1.604), anemia (OR 1.132), bone marrow dysfunction (ORR 1.471-1.645), and schizophrenia (ORR 1.287-1.556) showed significant association with infection of COVID-19. In terms of severity, diabetes (OR 1.417, 95% CI 1.047-1.917), hypertension (OR 1.378, 95% CI 1.008-1.883), heart failure (ORR 1.562-1.730), chronic lower respiratory disease (ORR 1.361-1.413), non-infectious lower digestive system disease (ORR 1.361-1.418), rheumatoid arthritis (ORR 1.865-1.908), substance use (ORR 2.790-2.848), and schizophrenia (ORR 3.434-3.833) were related with severe COVID-19. Conclusions: We identified several comorbidities associated with COVID-19. Health care workers should be more careful when diagnosing and treating COVID-19 when the patient has the above-mentioned comorbidities. Keywords: COVID-19, SARS-CoV-2, Comorbidity, Risk factor, Severity

Association of previous medications with the risk of COVID-19: a nationwide claims-based study from South Korea (preprint)

Background. Identifying the association between medications taken prior to the infection of coronavirus disease (COVID-19) might be useful during the current pandemic until a proven treatment is developed. We aimed to determine whether the risk of developing COVID-19 was associated with the use of various drugs that may increase or decrease susceptibility to severe acute respiratory syndrome coronavirus 2 infection and COVID-19. Methods and Findings: A case-control study was performed using a nationwide claims database of South Korea, where a large testing capacity has been available throughout the pandemic. Exposure was defined as the prescription of study drugs that would have been continued until 7 days before the testing for COVID-19. Adults were considered eligible if they were >=18 years old and tested for COVID-19. Among the 65,149 eligible subjects (mean age, 48.3 years; 49.4% male), 5,172 (7.9%) were diagnosed with COVID-19. Hydroxychloroquine was not significantly associated with the risk of COVID-19 (adjusted odds ratio [aOR], 1.48; 95% CI, 0.95-2.31). In the overall population, lower risks of COVID-19 were associated with the use of camostat (aOR, 0.45; 95% CI, 0.20-1.02) and amiodarone (aOR, 0.54; 95% CI, 0.33-0.89), although the differences were not significant in the subgroup analyses. Angiotensin receptor blockers were also associated with a slightly increased risk of COVID-19 (aOR, 1.13; 95% CI, 1.01-1.26), which was also not observed in the subgroup analysis. The study limitations include potential bias regarding the controls' characteristics, inability to determine prescription compliance, and a lack of information regarding the severity of underlying conditions. Conclusions. No medications were consistently associated with increased or decreased risks of COVID-19. These findings suggest that a more cautious approach is warranted for the clinical use of re-purposed drugs until the results are available from clinical trials.