Objectives: This study aimed to summarize the results of coronavirus disease 2019 (COVID-19) risk assessments and to examine the associations between risk levels and various indicators, including COVID-19 incidence, risk perception, community mobility, and government policy. Methods: The results of the risk assessment and the indicators utilized were summarized. From November 2021 to May 2022, the COVID-19 risk level was evaluated on a weekly basis, and its correlation with these indicators was analyzed. Data were obtained from press releases by the Korea Disease Control and Prevention Agency, regular surveys conducted by Hankook Research, and information available on the Google and Oxford websites. Results: Weekly risk assessments were conducted for 30 weeks, using different indices depending on the phases. Correlation analysis revealed the strongest positive correlation between risk level and risk perception (r=0.841). The risk level from “1-week lead” demonstrated a strong positive correlation with the time-varying reproduction number (Rt). Similarly, the risk level from “week lagged value” showed a strong positive correlation with the number of severe cases in the hospital. Conclusion At the time of risk assessment, the Rt precedes the risk level, while severe cases in hospitals follow. Therefore, the assessed risk level functioned as an early warning system. Risk perception demonstrated the strongest correlation with the risk level, suggesting consistency throughout the assessment period. Contextual indicators (e.g., risk perception) that consider time lags and implementation scales, could improve the evaluation of future risk assessment results, particularly when there are challenges in reflecting specific situations in coordinated emergency response.

Objectives: This study aimed to summarize the results of coronavirus disease 2019 (COVID-19) risk assessments and to examine the associations between risk levels and various indicators, including COVID-19 incidence, risk perception, community mobility, and government policy. Methods: The results of the risk assessment and the indicators utilized were summarized. From November 2021 to May 2022, the COVID-19 risk level was evaluated on a weekly basis, and its correlation with these indicators was analyzed. Data were obtained from press releases by the Korea Disease Control and Prevention Agency, regular surveys conducted by Hankook Research, and information available on the Google and Oxford websites. Results: Weekly risk assessments were conducted for 30 weeks, using different indices depending on the phases. Correlation analysis revealed the strongest positive correlation between risk level and risk perception (r=0.841). The risk level from “1-week lead” demonstrated a strong positive correlation with the time-varying reproduction number (Rt). Similarly, the risk level from “week lagged value” showed a strong positive correlation with the number of severe cases in the hospital. Conclusion At the time of risk assessment, the Rt precedes the risk level, while severe cases in hospitals follow. Therefore, the assessed risk level functioned as an early warning system. Risk perception demonstrated the strongest correlation with the risk level, suggesting consistency throughout the assessment period. Contextual indicators (e.g., risk perception) that consider time lags and implementation scales, could improve the evaluation of future risk assessment results, particularly when there are challenges in reflecting specific situations in coordinated emergency response.

Objectives: This study aimed to summarize the results of coronavirus disease 2019 (COVID-19) risk assessments and to examine the associations between risk levels and various indicators, including COVID-19 incidence, risk perception, community mobility, and government policy. Methods: The results of the risk assessment and the indicators utilized were summarized. From November 2021 to May 2022, the COVID-19 risk level was evaluated on a weekly basis, and its correlation with these indicators was analyzed. Data were obtained from press releases by the Korea Disease Control and Prevention Agency, regular surveys conducted by Hankook Research, and information available on the Google and Oxford websites. Results: Weekly risk assessments were conducted for 30 weeks, using different indices depending on the phases. Correlation analysis revealed the strongest positive correlation between risk level and risk perception (r=0.841). The risk level from “1-week lead” demonstrated a strong positive correlation with the time-varying reproduction number (Rt). Similarly, the risk level from “week lagged value” showed a strong positive correlation with the number of severe cases in the hospital. Conclusion At the time of risk assessment, the Rt precedes the risk level, while severe cases in hospitals follow. Therefore, the assessed risk level functioned as an early warning system. Risk perception demonstrated the strongest correlation with the risk level, suggesting consistency throughout the assessment period. Contextual indicators (e.g., risk perception) that consider time lags and implementation scales, could improve the evaluation of future risk assessment results, particularly when there are challenges in reflecting specific situations in coordinated emergency response.

Objectives: This study aimed to summarize the results of coronavirus disease 2019 (COVID-19) risk assessments and to examine the associations between risk levels and various indicators, including COVID-19 incidence, risk perception, community mobility, and government policy. Methods: The results of the risk assessment and the indicators utilized were summarized. From November 2021 to May 2022, the COVID-19 risk level was evaluated on a weekly basis, and its correlation with these indicators was analyzed. Data were obtained from press releases by the Korea Disease Control and Prevention Agency, regular surveys conducted by Hankook Research, and information available on the Google and Oxford websites. Results: Weekly risk assessments were conducted for 30 weeks, using different indices depending on the phases. Correlation analysis revealed the strongest positive correlation between risk level and risk perception (r=0.841). The risk level from “1-week lead” demonstrated a strong positive correlation with the time-varying reproduction number (Rt). Similarly, the risk level from “week lagged value” showed a strong positive correlation with the number of severe cases in the hospital. Conclusion At the time of risk assessment, the Rt precedes the risk level, while severe cases in hospitals follow. Therefore, the assessed risk level functioned as an early warning system. Risk perception demonstrated the strongest correlation with the risk level, suggesting consistency throughout the assessment period. Contextual indicators (e.g., risk perception) that consider time lags and implementation scales, could improve the evaluation of future risk assessment results, particularly when there are challenges in reflecting specific situations in coordinated emergency response.

Objectives: This study aimed to summarize the results of coronavirus disease 2019 (COVID-19) risk assessments and to examine the associations between risk levels and various indicators, including COVID-19 incidence, risk perception, community mobility, and government policy. Methods: The results of the risk assessment and the indicators utilized were summarized. From November 2021 to May 2022, the COVID-19 risk level was evaluated on a weekly basis, and its correlation with these indicators was analyzed. Data were obtained from press releases by the Korea Disease Control and Prevention Agency, regular surveys conducted by Hankook Research, and information available on the Google and Oxford websites. Results: Weekly risk assessments were conducted for 30 weeks, using different indices depending on the phases. Correlation analysis revealed the strongest positive correlation between risk level and risk perception (r=0.841). The risk level from “1-week lead” demonstrated a strong positive correlation with the time-varying reproduction number (Rt). Similarly, the risk level from “week lagged value” showed a strong positive correlation with the number of severe cases in the hospital. Conclusion At the time of risk assessment, the Rt precedes the risk level, while severe cases in hospitals follow. Therefore, the assessed risk level functioned as an early warning system. Risk perception demonstrated the strongest correlation with the risk level, suggesting consistency throughout the assessment period. Contextual indicators (e.g., risk perception) that consider time lags and implementation scales, could improve the evaluation of future risk assessment results, particularly when there are challenges in reflecting specific situations in coordinated emergency response.

Background: The advent of the omicron variant and the formulation of diverse therapeutic strategies marked a new epoch in the realm of coronavirus disease 2019 (COVID-19). Studies have compared the clinical outcomes between COVID-19 and seasonal influenza, but such studies were conducted during the early stages of the pandemic when effective treatment strategies had not yet been developed, which limits the generalizability of the findings.Therefore, an updated evaluation of the comparative analysis of clinical outcomes between COVID-19 and seasonal influenza is requisite. Methods: This study used data from the severe acute respiratory infection surveillance system of South Korea. We extracted data for influenza patients who were infected between 2018 and 2019 and COVID-19 patients who were infected in 2021 (pre-omicron period) and 2022 (omicron period). Comparisons of outcomes were conducted among the pre-omicron, omicron, and influenza cohorts utilizing propensity score matching. The adjusted covariates in the propensity score matching included age, sex, smoking, and comorbidities. Results: The study incorporated 1,227 patients in the pre-omicron cohort, 1,948 patients in the omicron cohort, and 920 patients in the influenza cohort. Following propensity score matching, 491 patients were included in each respective group. Clinical presentations exhibited similarities between the pre-omicron and omicron cohorts; however, COVID-19 patients demonstrated a higher prevalence of dyspnea and pulmonary infiltrates compared to their influenza counterparts. Both COVID-19 groups exhibited higher in-hospital mortality and longer hospital length of stay than the influenza group. The omicron group showed no significant improvement in clinical outcomes compared to the pre-omicron group. Conclusion The omicron group did not demonstrate better clinical outcomes than the pre-omicron group, and exhibited significant disease severity compared to the influenza group. Considering the likely persistence of COVID-19 infections, it is imperative to sustain comprehensive studies and ongoing policy support for the virus to enhance the prognosis for individuals affected by COVID-19.

Background: In order to minimize the spread of seasonal influenza epidemic to communities worldwide, the Korea Disease Control and Prevention Agency has issued an influenza epidemic alert using the influenza epidemic threshold formula based on the results of the influenza-like illness (ILI) rate. However, unusual changes have occurred in the pattern of respiratory infectious diseases, including seasonal influenza, after the coronavirus disease 2019 (COVID-19) pandemic. As a result, the importance of detecting the onset of an epidemic earlier than the existing epidemic alert system is increasing. Accordingly, in this study, the Time Derivative (TD) method was suggested as a supplementary approach to the existing influenza alert system for the early detection of seasonal influenza epidemics. Methods: The usefulness of the TD method as an early epidemic alert system was evaluated by applying the ILI rate for each week during past seasons when seasonal influenza epidemics occurred, ranging from the 2013–2014 season to the 2022–2023 season to compare it with the issued time of the actual influenza epidemic alert. Results: As a result of applying the TD method, except for the two seasons (2020–2021 season and 2021–2022 season) that had no influenza epidemic, an influenza early epidemic alert was suggested during the remaining seasons, excluding the 2017–2018 and 2022–2023 seasons. Conclusion The TD method is a time series analysis that enables early epidemic alert in real-time without relying on past epidemic information. It can be considered as an alternative approach when it is challenging to set an epidemic threshold based on past period information.This situation may arise when there has been a change in the typical seasonal epidemic pattern of various respiratory viruses, including influenza, following the COVID-19 pandemic.

Objectives: This study investigated the characteristics of coronavirus disease 2019 (COVID-19) among individuals with disabilities on a nationwide scale in the Republic of Korea, as limited research has examined this population. Methods: Between January 1 and November 30, 2021, a total of 5,687 confirmed COVID-19 cases among individuals with disabilities were reported through the Korea Disease Control and Prevention Agency’s COVID-19 web reporting system. Follow-up continued until December 24, and demographic, epidemiological, and clinical characteristics were analyzed. Results: Individuals with disabilities represented approximately 1.5% of confirmed cases, with a mean age of 58.1 years. Most resided in or near metropolitan areas (86.6%) and were male (60.6%). Frequent sources of infection included home (33.4%) and contact with confirmed cases (40.7%). Many individuals (75.9%) had underlying conditions, and 7.7% of cases were severe. People with disabilities showed significantly elevated risk of severe infection (adjusted odds ratio [aOR], 1.63; 95% confidence interval [CI], 1.47–1.81) and mortality (aOR, 1.65; 95% CI, 1.43–1.91). Vaccination against COVID-19 was associated with significantly lower risk of severe infection (aORs for the first, second, and third doses: 0.6 [95% CI, 0.42–0.85], 0.28 [95% CI, 0.22–0.35], and 0.16 [95% CI, 0.05–0.51], respectively) and death (adjusted hazard ratios for the first and second doses: 0.57 [95% CI, 0.35–0.93] and 0.3 [95% CI, 0.23–0.40], respectively). Conclusion Individuals with disabilities showed higher risk of severe infection and mortality from COVID-19. Consequently, it is critical to strenghthenCOVID-19 vaccination initiatives and provide socioeconomic assistance for this vulnerable population.

Background: Nonpharmacological interventions (NPIs) reduce the incidence of respiratory infections. After NPIs imposed during the coronavirus disease 2019 pandemic ceased, respiratory infections gradually increased worldwide. However, few studies have been conducted on severe respiratory infections requiring hospitalization in pediatric patients.This study compares epidemiological changes in severe respiratory infections during pre-NPI, NPI, and post-NPI periods in order to evaluate the effect of that NPI on severe respiratory infections in children. Methods: We retrospectively studied data collected at 13 Korean sentinel sites from January 2018 to October 2022 that were lodged in the national Severe Acute Respiratory Infections (SARIs) surveillance database. Results: A total of 9,631 pediatric patients were admitted with SARIs during the pre-NPI period, 579 during the NPI period, and 1,580 during the post-NPI period. During the NPI period, the number of pediatric patients hospitalized with severe respiratory infections decreased dramatically, thus from 72.1 per 1,000 to 6.6 per 1,000. However, after NPIs ceased, the number increased to 22.8 per 1,000. During the post-NPI period, the positive test rate increased to the level noted before the pandemic. Conclusion Strict NPIs including school and daycare center closures effectively reduced severe respiratory infections requiring hospitalization of children. However, childcare was severely compromised. To prepare for future respiratory infections, there is a need to develop a social consensus on NPIs that are appropriate for children.

Objectives: This study aimed to assess the scale and transmission patterns of coronavirus disease 2019 (COVID-19) in a religious village community in South Korea, to determine the risk factors of transmission, and to evaluate vaccine effectiveness. Methods: An epidemiological survey was conducted, and data were collected and analyzed from 602 villagers in the religious village community. Multivariate logistic regression analysis was used to identify the risk factors for COVID-19 transmission and to evaluate vaccine effectiveness. Results: The outbreak attack rate was 72.1% (434/602). The attack rate was high among women in their 60s, the unemployed, residents living near religious facility (<500 m), and the unvaccinated. Age, the distance between religious facility and residences, and the absence of vaccination were identified as risk factors for infection. Vaccine effectiveness was 49.0%, and the highest effectiveness was seen in the age group of 59 years or younger (65.8%). Conclusion This village community was isolated, with little communication with the outside world. However, the frequency of close contact between residents was relatively high, contributing to the spread of COVID-19 in the village even with relatively short exposure. Vaccination rates in the village community were also lower than those in the general public. Public health authorities should consider the potential impact of cultural factors, including religion, that could lead to the exponential spread of COVID-19 in closed village communities.