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Patients with weak or no symptoms accelerate the spread of COVID-19 through various mutations and require more aggressive and active means of validating the COVID-19 infection. More than 30% of patients are reported as asymptomatic infection after the delta mutation spread in Korea. It means that there is a need for a means to more actively and accurately validate the infection of the epidemic via pre-symptomatic detection, besides confirming the infection via the symptoms. Mishara et al. (Nat Biomed Eng 4, 1208–1220, 2020) reported that physiological data collected from smartwatches could be an indicator to suspect COVID-19 infection. It shows that it is possible to identify an abnormal state suspected of COVID-19 by applying an anomaly detection method for the smartwatch's physiological data and identifying the subject's abnormal state to be observed. This paper proposes to apply the One Class-Support Vector Machine (OC-SVM) for pre-symptomatic COVID-19 detection. We show that OC-SVM can provide better performance than the Mahalanobis distance-based method used by Mishara et al. (Nat Biomed Eng 4, 1208–1220, 2020) in three aspects: earlier (23.5–40% earlier) and more detection (13.2–19.1% relative better) and fewer false positives. As a result, we could conclude that OC-SVM using Resting Heart Rate (RHR) with 350 and 300 moving average size is the most recommended technique for COVID-19 pre-symptomatic detection based on physiological data from the smartwatch. [ABSTRACT FROM AUTHOR]

To model the COVID-19 infection and develop effective control measures, this paper proposes an SEIR-type epidemic model considering the impact of face-mask wearing and vaccination. Firstly, the effective reproduction number and the threshold conditions are obtained. Secondly, based on the data of South Korea from January 20, 2022 to March 21, 2022, the model parameters are estimated. Finally, a sensitivity analysis and the numerical study are conducted. The results show that the face-mask wearing is associated with 83 % and 90 % reductions in the numbers of cumulative cases and newly confirmed cases, respectively, after a period of 60 days, when the face mask wearing rate increases by 15 % . Furthermore, the vaccination rate is associated with 75 % and 80 % reductions in the numbers of cumulative cases and the newly confirmed cases, respectively, after the same period of 60 days when the vaccination rate is increased by 15 % . A combined measure involving face-mask wearing and vaccination may be more effective and reasonable in preventing and controlling this infection. It is also suggested that disease control departments should strongly recommended the wearing of face masks s as well as vaccination to prevent the unvaccinated people from becoming infected. [ABSTRACT FROM AUTHOR]

Early forecasting of COVID-19 virus spread is crucial to decision making on lockdown or closure of cities, states or countries. In this paper we design a recursive bifurcation model for analyzing COVID-19 virus spread in different countries. The bifurcation facilitates recursive processing of infected population through linear least-squares fitting. In addition, a nonlinear least-squares fitting procedure is utilized to predict the future values of infected populations. Numerical results on the data from two countries (South Korea and Germany) indicate the effectiveness of our approach, compared to a logistic growth model and a Richards model in the context of early forecast. The limitation of our approach and future research are also mentioned at the end of this paper. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has swept the globe, and countries have responded with various intervention policies to prevent its spread. In this study, we aim to analyze the effectiveness of intervention policies implemented in South Korea. We use a stochastic individual-based model (IBM) with a synthetic population to simulate the spread of COVID-19. Using statistical data, we make the synthetic population and assign sociodemographic attributes to each individual. Individuals go about their daily lives based on their assigned characteristics, and encountering infectors in their daily lives stochastically determines whether they are infected. We reproduce the transmission of COVID-19 using the IBM simulation from November 2020 to February 2021 when three phases of increasingly stringent intervention policies were implemented, and then assess their effectiveness. Additionally, we predict how the spread of infection would have been different if these policies had been implemented in January 2022. This study offers valuable insights into the effectiveness of intervention policies in South Korea, which can assist policymakers and public health officials in their decision-making process. [ABSTRACT FROM AUTHOR]

An amendment to this paper has been published and can be accessed via a link at the top of the paper. [ABSTRACT FROM AUTHOR]

Little is known about the prevalence of chronic kidney disease (CKD) during the coronavirus disease 2019 (COVID-19) pandemic. We aimed to investigate the long-term trends in CKD prevalence from South Korea including the early pandemic. We used data from 108,152 Korean adults from 2007 to 2020 obtained from a representative longitudinal serial study. We defined CKD as a condition when the participant's estimated glomerular filtration rate was < 60 mL/min/1.73 m2, or one-time spot proteinuria was ≥ 1 +, and then examined the overall trends in the prevalence of CKD. Among the included adults (n = 80,010), the overall national prevalence of CKD was 6.2%. The trend slope gradually increased from 2007 to 2019, however, there was a sudden decrease in 2020 (2007–2010, 5.1% [95% confidence interval (CI) 4.7–5.5]; 2017–2019, 7.1% [95% CI 6.6–7.6]; pandemic period, 6.5% [95% CI 5.7–7.3]; and βdiff, − 0.19; 95% CI − 0.24 to − 0.13). The prevalence of CKD among younger adults and those with poor medical utilization significantly decreased during the early pandemic. This study was the first large-scale study to investigate the longitudinal prevalence of CKD from 2007 to 2020. Further research is needed to fully understand the exact causes for this decline and to identify healthcare policy strategies for preventing and managing CKD. [ABSTRACT FROM AUTHOR]

Burnout is a form of negative emotional and physical response to job stress. This study aimed to investigate the prevalence of burnout among healthcare workers responding to the coronavirus disease 2019 (COVID-19) outbreak in Korea and to explore correlates of burnout among healthcare workers. A nationwide questionnaire-based survey was conducted from December 1, 2020, to January 29, 2021 on 1425 healthcare workers who worked in one of the 16 healthcare facilities designated for COVID-19 care, in public health centers, or as paramedics in Korea. Burnout was assessed using 16 Korean-adapted items based on the Oldenburg Burnout Inventory (OLBI). Data were collected using a structured questionnaire and analyzed using the R version 4.1.1 software program. OLBI results indicate clinically exhaustion in 84.5% (1204/1425) and clinically disengagement in 91.1% (1298/1425), and 77.3% (1102/1425) met the score criteria for both the exhaustion and disengagement subscales for burnout. Burnout rate was significantly increased in the group with chronic fatigue symptoms (Fatigue Severity Scale ≥ 3.22) after the outbreak of COVID-19 (OR, 3.94; 95% CI 2.80–5.56), in the female group (OR, 2.05; 95% CI 1.46–2.86), in the group with physical symptoms (Patient Health Questionnaire-15 ≥ 10) after the outbreak of COVID-19 (OR, 2.03; 95% CI 1.14–3.60), in the group with a higher Global Assessment of Recent Stress scale (OR, 1.71; 95% CI 1.46–2.01), in the group with post-traumatic stress symptoms (Primary Care Post-Traumatic Stress Disorder-5 ≥ 2) (OR, 1.47; 95% CI 1.08–2.01), and in the younger age group(OR, 1.45; 95% CI 1.22–1.72). The chronic fatigue symptoms were correlated with cumulative days of care (OR, 1.18; 95% CI 1.02–1.37). The physical symptoms were correlated with average contact hours with COVID-19 patients per day (OR, 1.34; 95% CI 1.17–1.54), and cumulative days of care (OR, 1.21; 95% CI 1.06–1.38). Most Korean healthcare workers suffered from burnout related to excessive workload during the COVID-19 pandemic. During a widespread health crisis like COVID-19, it is necessary to regularly check the burnout status in healthcare workers and reduce their excessive workload by supplementing the workforce and providing appropriate working hours sufficient rest hours. [ABSTRACT FROM AUTHOR]

This study undertook to determine the changes in the numbers of outpatient visits for various ophthalmic diseases during the COVID-19 pandemic compared with before. The monthly outpatient visits for 14 common ophthalmic diseases were enumerated based on the ICD-10 codes in Korean National Health Insurance Service data. The differences in the mean outpatient visits and disease variance 'before' and 'during COVID-19' were calculated. Subsequently, subgroup analyses according to age and sex were performed. The number of outpatient visits for conjunctivitis, scleritis & episcleritis, keratitis, cataract, diabetic retinopathy, and traumatic ophthalmic disease were lower during than before COVID-19 (all P < 0.001). The lower numbers of outpatient visits for ophthalmic disorders during COVID-19 were consistent across the age and sex subgroups. All ophthalmic diseases other than endophthalmitis showed no change of variation 'during' relative to 'before' COVID-19. In conclusion, during the COVID-19 pandemic, the ophthalmic outpatient visits decreased for infectious and inflammatory diseases, screening diseases, and traumatic diseases. However, COVID-19 is not considered to have had a significant effect on variation. [ABSTRACT FROM AUTHOR]

The evidence for the impact of benzodiazepine (BZD) use on infection or clinical outcomes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is limited. We evaluated the association of BZD use with SARS-CoV-2 infection and the clinical outcomes of coronavirus disease 2019 (COVID-19) using a nationwide COVID-19 database from South Korea. This nationwide cohort study was performed using the COVID-19 database from the Health Insurance Review and Assessment Service of Korea, and SARS-CoV-2 positivity was investigated according to BZD use. SARS-CoV-2-positive adult patients were assessed in three groups, those who needed hospitalization, those with severe symptoms requiring intensive care, and those who died. A multivariate logistic regression model was used for all the analyses. After adjusting for potential confounding factors, there was no association between BZD use and SARS-CoV-2 positivity. SARS-CoV-2-positive patients with BZD use showed an increased risk of need for hospitalization from COVID-19 compared to those without BZD use (odds ratio [OR]: 1.33, 95% confidence interval [CI] 1.07–1.65). In addition, there was a higher risk for long-term users (OR: 2.64, 95% CI 1.08–6.47). Chronic BZD use contributed to a higher risk of the need for hospitalization among COVID-19 patients, whereas BZD use did not increase the risk of SARS-CoV-2 test positivity, severe outcomes, or mortality. [ABSTRACT FROM AUTHOR]

Apart from the incidence and mortality caused by it, Coronavirus disease (COVID-19) has had a significant impact on other diseases. This study aimed to estimate the influences of COVID-19 pandemic on the incidence of tuberculosis (TB) and the number of TB-associated deaths in Republic of Korea. A dynamic compartment model incorporating age-structure was developed for studying TB transmission and progression using the Korean population data. After calibration with notification of incidence data from South Korea, the TB burden over 6 years (2020–2025) was predicted under the nine different scenarios. Under the scenario of strong social distancing and low-level health service disruption, new TB cases were reduced by 761 after 1 year in comparison to the baseline. However, in the elderly population, social distancing had little impact on TB incidence. On the other hand, the number of TB-related deaths mainly depends on the level of health service disruption for TB care. It was predicted that with a high degree of health service disruption, the number of TB-related deaths would increase up to 155 in 1 year and 80 percent of the TB-related deaths would be in the elderly population. The decrease of tuberculosis incidence is significantly affected by social distancing, which is owing to reduction of contacts. The impact of health service disruption is dominant on TB-related deaths, which occurs mainly in the elderly. It suggests that it is important to monitor TB-related deaths by COVID-19 because the TB burden of the elderly is high in the Republic of Korea. [ABSTRACT FROM AUTHOR]

The experience of the early nationwide COVID-19 pandemic in South Korea led to an early shortage of medical resources. For efficient resource allocation, accurate prediction of the prognosis or mortality of confirmed patients is essential. Therefore, the aim of this study was to develop an accurate model for predicting COVID-19 mortality using epidemiolocal and clinical variables and for identifying a high-risk group of confirmed patients. Clinical and epidemiolocal variables of 4049 patients with confirmed COVID-19 between January 20, 2020 and April 30, 2020 collected by the Korean Disease Control and Prevention Agency were used. Among the 4049 total confirmed patients, 223 patients died, while 3826 patients were released from isolation. Patients who had the following risk factors showed significantly higher risk scores: age over 60 years, male sex, difficulty breathing, diabetes, cancer, dementia, change of consciousness, and hospitalization in the intensive care unit. High accuracy was shown for both the development set (n = 2467) and the validation set (n = 1582), with AUCs of 0.96 and 0.97, respectively. The prediction model developed in this study based on clinical features and epidemiological factors could be used for screening high-risk groups of patients and for evidence-based allocation of medical resources. [ABSTRACT FROM AUTHOR]

A novel severe acute respiratory syndrome coronavirus 2 emerged in December 2019, and it took only a few months for WHO to declare COVID-19 as a pandemic in March 2020. It is very challenging to discover complex spatial–temporal transmission mechanisms. However, it is crucial to capture essential features of regional-temporal patterns of COVID-19 to implement prompt and effective prevention or mitigation interventions. In this work, we develop a novel framework of compatible window-wise dynamic mode decomposition (CwDMD) for nonlinear infectious disease dynamics. The compatible window is a selected representative subdomain of time series data, in which compatibility between spatial and temporal resolutions is established so that DMD can provide meaningful data analysis. A total of four compatible windows have been selected from COVID-19 time-series data from January 20, 2020, to May 10, 2021, in South Korea. The spatiotemporal patterns of these four windows are then analyzed. Several hot and cold spots were identified, their spatial–temporal relationships, and some hidden regional patterns were discovered. Our analysis reveals that the first wave was contained in the Daegu and Gyeongbuk areas, but it spread rapidly to the whole of South Korea after the second wave. Later on, the spatial distribution is seen to become more homogeneous after the third wave. Our analysis also identifies that some patterns are not related to regional relevance. These findings have then been analyzed and associated with the inter-regional and local characteristics of South Korea. Thus, the present study is expected to provide public health officials helpful insights for future regional-temporal specific mitigation plans. [ABSTRACT FROM AUTHOR]

We developed a tool to guide decision-making for early triage of COVID-19 patients based on a predicted prognosis, using a Korean national cohort of 5,596 patients, and validated the developed tool with an external cohort of 445 patients treated in a single institution. Predictors chosen for our model were older age, male sex, subjective fever, dyspnea, altered consciousness, temperature ≥ 37.5 °C, heart rate ≥ 100 bpm, systolic blood pressure ≥ 160 mmHg, diabetes mellitus, heart disease, chronic kidney disease, cancer, dementia, anemia, leukocytosis, lymphocytopenia, and thrombocytopenia. In the external validation, when age, sex, symptoms, and underlying disease were used as predictors, the AUC used as an evaluation metric for our model's performance was 0.850 in predicting whether a patient will require at least oxygen therapy and 0.833 in predicting whether a patient will need critical care or die from COVID-19. The AUCs improved to 0.871 and 0.864, respectively, when additional information on vital signs and blood test results were also used. In contrast, the protocols currently recommended in Korea showed AUCs less than 0.75. An application for calculating the prognostic score in COVID-19 patients based on the results of this study is presented on our website (https://nhimc.shinyapps.io/ih-psc/), where the results of the validation ongoing in our institution are periodically updated. [ABSTRACT FROM AUTHOR]