Policy Review and Modeling Analysis of Mitigation Measures for Coronavirus Disease Epidemic Control, Health System, and Disease Burden, South Korea.

We reviewed the timeline of key policies for control of the coronavirus disease epidemic and determined their impact on the epidemic and hospital burden in South Korea. Using a discrete stochastic transmission model, we estimated that multilevel policies, including extensive testing, contact tracing, and quarantine, reduced contact rates by 90% and rapidly decreased the epidemic in Daegu and nationwide during February‒March 2020. Absence of these prompt responses could have resulted in a >10-fold increase in infections, hospitalizations, and deaths by May 15, 2020, relative to the status quo. The model suggests that reallocation of persons who have mild or asymptomatic cases to community treatment centers helped avoid overwhelming hospital capacity and enabled healthcare workers to provide care for more severely and critically ill patients in hospital beds and negative-pressure intensive care units. As small outbreaks continue to occur, contact tracing and maintenance of hospital capacity are needed.

Characteristics in Pediatric Patients with Coronavirus Disease 2019 in Korea.

BACKGROUND: Based on the reports of low prevalence and severity of pediatric severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections, the Korean government has released new SARS-CoV-2 infection response and treatment guidelines for children under the age of 12 years. The government has further directed school reopening under strict preventive measures. However, there is still considerable concern on the impact of school reopening on community transmission of Coronavirus disease 2019 (COVID-19). In the present study, we aimed to evaluate the appropriateness of these directives and the severity of SARS-CoV-2 infections in children as compared to adults using sufficient national sample data. METHODS: In the present study, we evaluated the severity of SARS-CoV-2 infection in pediatric patients as compared to adults by analyzing the length of hospital stays (LOS), medical expenses, and hospital and intensive care unit (ICU) admission rates. A multivariate linear regression analysis was carried out to examine the effects of COVID-19 patients that the characteristics on the LOS and medical expenses, and multivariate logistic regression analysis were performed to identify COVID-19 characteristics that affect hospital and ICU admission rates and to prove the low SARS-CoV-2 infection severity in pediatric patients. RESULTS: The hospitalization period for children aged 0-9 was 37% shorter and that of patients aged 10-19 years was 31% shorter than those of older age groups (P < 0.001). The analysis of the medical expenses by age showed that on average, medical expenses for children were approximately 4,900 USD lower for children than for patients over 80 years of age. The linear regression analysis also showed that patients who were 0-9 years old spent 87% and those aged 10-19 118% less on medical expenses than those aged 70 and over, even after the correction of other variables (P < 0.001). The probability of hospitalization was the lowest at 10-19 years old (odds ratio [OR], 0.05; 95% confidence interval [CI], 0.03-0.09), and their ICU admission rate was also the lowest at 0.14 (OR, 0.14; 95% CI, 0.08-0.24). On the other hand, the likelihood of hospitalization and ICU admission was the highest in children aged 0-9 years, and among patients under the age of 50 years in general. CONCLUSION: This study demonstrated the low severity of SARS-CoV-2 infection in younger patients (0-19 years) by analyzing the LOS, medical expenses, hospital, and intensive care unit admission rates as outcome variables. As the possibility to develop severe infection of coronavirus at the age of 10-19 was the lowest, a mitigation policy is also required for middle and high school students. In addition, children with underlying diseases need to be protected from high-risk infection environments.

Association of Metabolic Syndrome with COVID-19 in the Republic of Korea.

BACKGROUND: Metabolic syndrome (MetS) is reportedly a crucial risk factor for coronavirus disease 2019 (COVID-19). Since the epidemiological studies that examine this association are few and include small samples, we investigated the relationship between MetS and COVID-19 severity and death using a larger sample in the Republic of Korea. METHODS: We analyzed 66,321 patients, 4,066 of whom had COVID-19. We used chi-square tests to examine patients' characteristics. We performed logistic regression analysis to analyze differences in COVID-19 infection and clinical outcomes according to the presence of MetS. RESULTS: Although MetS was not significantly associated with COVID-19 risk, acquiring MetS was significantly associated with the risk of severe COVID-19 outcomes (odds ratio [OR], 1.97; 95% confidence interval [CI], 1.34 to 2.91; P=0.001). The mortality risk was significantly higher in COVID-19 patients with MetS (OR, 1.74; 95% CI, 1.17 to 2.59; P=0.006). Patients with abnormal waist circumference were approximately 2.07 times more likely to develop severe COVID-19 (P<0.001), and high-density lipoprotein cholesterol (HDL-C) levels were significantly associated with COVID-19; the mortality risk due to COVID-19 was 1.74 times higher in men with an HDL-C level of <40 mg/dL and in women with an HDL-C level of <50 mg/dL (P=0.012). CONCLUSION: COVID-19 is likely associated with severity and death in patients with MetS or in patients with MetS risk factors. Therefore, patients with MetS or those with abnormal waist circumference and HDL-C levels need to be treated with caution.

Exposure to COVID-19 Infection and Mortality Rates Among People With Disabilities in South Korea.

BACKGROUND: With the delayed eradication of coronavirus disease 2019 (COVID-19), people with disabilities, a socially vulnerable class of individuals, face aggravated hardships caused by a pause in support services and lack of care due to stricter social distancing policies combined with the challenges of their disabilities. Given this background, we aim to investigate COVID-19 infection and mortality rates among people with disabilities, who face heightened physical and mental health threats amidst the COVID-19 pandemic. METHODS: Gender, age, health insurance premiums, the Charlson Comorbidity Index (CCI), the severity of the disability, and the type of disability were compared among people with disabilities who had been infected with or died from COVID-19 using the nationally representative National Health Insurance Service (NHIS)-COVID-19 database (DB). RESULTS: We found that the COVID-19 infection rate was higher among those with low income, those with severe disability, and those with "other" disabilities (ie, speech disabilities, hepatic dysfunction, respiratory dysfunction, facial disfigurement, intestinal fistular/urinary disability, epilepsy, intellectual disability, autistic disorder, and mental disorders). The mortality rate was markedly higher (ie, 15.90 times higher, odds ratio [OR]: 15.90, 95% confidence interval [CI]: 6.16 - 41.06) among people aged 80 years or older as compared with those aged 60 years or younger. The odds for mortality were 2.49 times higher (OR: 2.49, 95% CI: 1.33 - 4.64) among people with severe disabilities as compared with mild disabilities. CONCLUSION: Among people with disabilities, we found that COVID-19 infection rates differed according to income level, severity of the disability, and disability type, while the COVID-19 mortality rates differed according to age and severity of the disability.

Analysis of Risk Factors on Readmission Cases of COVID-19 in the Republic of Korea: Using Nationwide Health Claims Data.

In South Korea, 4.5% patients of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were readmitted to hospitals after discharge. However, there is insufficient research on risk factors for readmission and management of patients after discharge is poor. In this study, 7590 confirmed coronavirus disease (COVID-19) patients were defined as a target for analysis using nationwide medical claims data. The demographic characteristics, underlying diseases, and the use of medical resources were used to examine the association with readmission through the chi-square test and then logistic regression analysis was performed to analyze factors affecting readmission. Of the 7590 subjects analyzed, 328 patients were readmitted. The readmission rates of men, older age and patients with medical benefits showed a high risk of readmission. The Charlson Comorbidity Index score was also related to COVID-19 readmission. Concerning requiring medical attention, there was a higher risk of readmission for the patients with chest radiographs, computed tomography scans taken and lopinavir/ritonavir at the time of their first admission. Considering the risk factors presented in this study, classifying patients with a high risk of readmission and managing patients before and after discharge based on priority can make patient management and medical resource utilization more efficient. This study also indicates the importance of lifestyle management after discharge.

Intensive Care Unit Capacity and Its Associated Risk Factors During the COVID-19 Surge in the Republic of Korea: Analysis Using Nationwide Health Claims Data.

OBJECTIVE: To identify risk factors for intensive care unit (ICU) admission and mechanical ventilator usage among confirmed coronavirus disease (COVID-19) patients and estimate the effects of mitigation efforts on ICU capacity in Korea. PATIENTS AND METHODS: Data on profiles and medical history of all confirmed COVID-19 patients in the past 1 year were extracted from the Korean National Health Insurance System's claims database to assess risk factors for ICU admission and ventilator use. We used a time-series epidemic model to estimate the ICU census in Daegu from the reported hospital data. FINDINGS: Multivariate regression analysis revealed male sex, old age, and residing in Daegu city as significant risk factors for ICU admission. The number of patients requiring ICU admission exceeded the bed capacity across all Daegu hospitals before March 9, 2020, and therefore, critically ill patients were transferred to nearby hospitals outside Daegu. This finding was consistent with our prediction that the ICU census in Daegu would peak on March 16, 2020, at 160 through mitigation efforts, without which it would have reached 300 by late March 2020. CONCLUSION: Older age and male sex were risk factors for ICU admission. In addition, the geographic location of the hospital seems to contribute to the severity of the COVID-19 patients admitted to the ICU and to the ICU capacity.