The Impact of teledermatology during the COVID-19 pandemic.

Teledermatology has been widely adopted during the COVID-19 pandemic as virtual patient care promotes social distancing and decreases viral exposure risk. As teledermatology has become more prominent during this period, it is essential to assess whether virtual visits allow for adequate patient care. To assess perceptions of advantages and disadvantages of teledermatology, a survey was sent to academic dermatologists through the Association of Professors of Dermatology (APD) listserv. Of the physicians surveyed, 94% reported their departments had implemented teledermatology during the COVID-19 pandemic. The majority (64%) described teledermatology as an effective tool for patient care because of improved access to care, decreased risk of COVID-19 exposure, and convenience. Frequently cited limitations of teledermatology were image quality, technical difficulties, and inability to perform a comprehensive skin examination. Thirty-seven percent of respondents reported teledermatology as a contributor to their professional burnout. Although teledermatology has become more prevalent as a result of the pandemic, its role moving forward is uncertain given its limitations.

The impact of the coronavirus disease 2019 pandemic on dermatologist burnout: a survey study.

Burnout in dermatology is on the rise, with 36% of U.S. dermatologists experiencing burnout in 2020. The coronavirus disease 2019 (COVID-19) pandemic may exacerbate this problem with healthcare workers reporting increased anxiety, depression, and insomnia. To assess the rate, severity, and causes of burnout before and during the pandemic, a survey was sent to academic dermatologists through the Association of Professors of Dermatology (APD) listserv and compared to a similar survey administered to the same population prior to the pandemic. Burnout rates have increased from 2018, with 53% of participants experiencing burnout once a week or more and 17% experiencing burnout daily during the pandemic. The most common COVID-related burnout factors involve uncertainty about the future, teledermatology, fear of exposing loved ones to COVID-19, and compensation reduction. The challenges posed by the COVID-19 pandemic compound existing burnout within dermatology, warranting consideration by academic institutions.

Sensing contacts, coughs, and hand hygiene

Detailed contact tracing that not only captures the social interaction graph, but also precise interaction distance and duration could prove useful in a wide variety of applications. Most notably, we have seen this play out in the global COVID-19 pandemic, where social distancing and contact tracing have proven critical in efforts to combat disease spread. Traditionally, contact tracing has relied on manual reporting, which provides only coarse grained data and relies on the subjectivity of human memory. These factors have led to a drive for wearable sensor based solutions which can provide objective face-to-face interaction data. Ideally, these sensors would provide precise interaction distances and durations, and would only report these metrics when users are actually facing each other and are not separated by a barrier. Current contact tracing sensors can generally be divided into two camps. First are sensors that can provide precise interaction distances, but require infrastructure to run, making them difficult to deploy in practice. Second are sensors that do not require infrastructure, but only provide a rough sense of proximity, making it difficult to analyze which interactions are significant. The majority of these systems also cannot determine if there is a barrier separating users, or if the users are facing each other.To address these issues, we present Opo, a wearable sensor which requires no infrastructure to run, provides interaction distance accurate to 5~cm, and only records interaction distances when users are facing each other with no barriers between them. The key problem we identify is that systems that provide precise interaction distances require RF based neighbor discovery protocols to synchronize nodes before performing ranging operations to get interaction distance. Instead, Opo utilizes ultrasonic passive vigilance, to perform neighbor discovery and ranging at the same time, lowering system complexity and power usage. In addition, while current wearables for contact tracing have largely focused on detecting interactions, in practice this information is greatly enriched by knowledge of health behaviors and symptoms. For example, researchers are often interested in detecting hand-washing behavior due to its importance in combating a wide variety of infectious diseases. Current hand washing sensor systems generally use wrist mounted accelerometers or utilize smart badges and soap-dispenser mounted sensors. Of these two system types, only smart badge plus soap dispenser sensor systems are able to capture if a person uses soap, a key consideration when measuring hand washing behavior. However, smart badge systems only detect when a person washes their hands with soap, and do not sense hand washing duration. The key problem is that current smart badge systems use low-resolution ranging technologies, making it difficult for them to determine when a user approaches leaves a sink. To address this problem, we create a smart badge plus dispenser mounted sensor system by extending Opo with passive vigilance in the accelerometric domain. This extension allows soap dispenser mounted Opos to passively detect when a dispenser is used and provide precise times when a user approaches and leaves a sink. To the best of our knowledge, our hand washing system is the first that can detect and categorize both soaped and un-soaped hand washing events and measure hand washing duration. Researchers are also often interested in when people first experience symptom onsets. In particular, researchers are often interested in when people begin coughing, due to its prominence as an early symptom in many infectious diseases. Current cough sensing systems focus on counting the number of times a person coughs over a given period of time. (PsycInfo Database Record (c) 2021 APA, all rights reserved)