Background: The coronavirus disease 2019 (COVID-19) pandemic has posed significant global public health challenges and created a substantial economic burden. Korea has experienced an extensive outbreak, which was linked to a religion-related super-spreading event. However, the implementation of various non-pharmaceutical interventions (NPIs), including social distancing, spring semester postponing, and extensive testing and contact tracing controlled the epidemic. Herein, we estimated the effectiveness of each NPI using a simulation model. Methods: A compartment model with a susceptible-exposed-infectious-quarantinedhospitalized structure was employed. Using the Monte-Carlo-Markov-Chain algorithm with Gibbs' sampling method, we estimated the time-varying effective contact rate to calibrate the model with the reported daily new confirmed cases from February 12th to March 31st (7 weeks). Moreover, we conducted scenario analyses by adjusting the parameters to estimate the effectiveness of NPI. Results: Relaxed social distancing among adults would have increased the number of cases 27.4-fold until the end of March. Spring semester non-postponement would have increased the number of cases 1.7-fold among individuals aged 0-19, while lower quarantine and detection rates would have increased the number of cases 1.4-fold. Conclusion: Among the three NPI measures, social distancing in adults showed the highest effectiveness. The substantial effect of social distancing should be considered when preparing for the 2nd wave of COVID-19.

The alcohol flushing response is experienced by 36–45% of East Asians after they consume a small amount of alcohol. Because individuals with this response are unable to metabolize the toxic acetaldehyde derived from alcohol effectively, the response offers a potential indicator of the health risks associated with alcohol intake. Depression is a major health problem linked to alcohol consumption; it might also be associated with the alcohol flushing response. Therefore, we examined the association between the alcohol flushing response and the risk of depression in the general population of South Korea. Our analysis included 139,380 participants and used data from the 2019 Korean Community Health Survey. Only current drinkers were considered in the analysis. The relationship between the alcohol flushing response and depression was evaluated by logistic regression analysis using SAS 9.4. Of the participants, more than one-third were current flushers; compared to never flushers, current flushers had a significantly greater risk of depression (adjusted odds ratio [AOR] 1.23, 95% confidence interval [CI] 1.12–1.34, P < 0.001). Former flushers did not exhibit a risk of depression. The risk of depression was significantly greater among alcohol flushers who drank < 15 g alcohol/day (< 5 g alcohol/day: AOR 1.20, 95% CI 1.07–1.35, P = 0.002; 5–14.9 g alcohol/day: AOR 1.39, 95% CI 1.13–1.70, P = 0.002). In conclusion, a large number of South Koreans experience the alcohol flushing response; compared with never flushers, current flushers are more likely to develop depression with a small dose of alcohol (< 15 g alcohol/day).

High connectivity between nations facilitates the spread of infectious diseases. We introduce an improved measure to estimate the risk of COVID-19 importation. The measure was applied to identify the effectiveness of travel-related control measures. We estimated the risk of importation, using the product of air-travel volume and COVID-19 prevalence in the area-of-origin. Travel volumes were acquired through real-time mobile data, and prevalence was calculated considering the time-varying strength of the COVID-19 testing policy. With the measure, the number of expected-imported cases was calculated, and compared with the reported-imported COVID-19 cases before and after post-entry quarantine for all entrants. The expected and reported-imported cases were well fitted (R2 = 0.8). A maximum of 35 undetected-imported cases was estimated to have entered Seoul, before the first imported COVID-19 case was confirmed. With the travel-related control measures, at most, 48 (73%) imported cases could be isolated from the local community. Our measure predicted trends in imported COVID-19 cases well. The method used to develop the measure can be applied to future emerging infectious diseases. Our results provide a ‘real-world’ evidence that travel-related control measures are effective at curbing further COVID-19 transmission.

BACKGROUND Earable devices are novel, interactive wearable-IoT devices that are user-friendly and have potential applications in mobile healthcare. The position of the ear is advantageous for assessing vital status and detecting diseases through reliable and comfortable sensing devices. OBJECTIVE Our study aims to review the utility of health-related indicators derived from earable devices for disease prevention. We also propose future directions for research on the healthcare applications of earable devices. METHODS A systematic review was conducted of the PubMed, Google Scholar, and EMBASE databases. Keywords were used to identify studies on earable devices published between 2015 and 2020. Fifty-one articles met the inclusion criteria and were reviewed. RESULTS The earable devices were described in terms of target health outcomes, biomarkers, sensor types and positions, and their utility for disease prevention. Dietary status was determined based on muscle movements and PPG. Brain status was measured by electroencephalography (EEG), and head injuries were detected by motion sensors. Heart status was measured, and cardiovascular diseases (CVDs) detected, using electrocardiography (ECG) and photoplethysmography (PPG). Most indicators were related to secondary prevention, but dietary indicators were also relevant to primary prevention. Tongue motion, gait form, diet habit, facial expression has potential as an indicator in tertiary prevention/rehabilitation. The most used sensor type was the electric sensor, to collect EEG, ECG, and electromyography (EMG) data. In almost half of the studies, the sensor was positioned within the ear canal, although other positions were also used, including behind and around the ear. CONCLUSIONS Earable devices can provide biomarkers for various health outcomes. Brain status and CVD were the most frequently targeted outcomes among the studies. Earable devices were mostly used for secondary prevention via monitoring of health or disease status. Potential utility of earable devices for primary and tertiary prevention needs to be further explored. Earable devices connected to smartphones or tablets through cloud servers will guarantee user access to personal health information and facilitate comfortable wearing.

The authors have withdrawn this preprint due to erroneous posting.