Corrigendum to: Temporal Changes in the Risk of Superspreading Events of Coronavirus Disease 2019.

[This corrects the article DOI: 10.1093/ofid/ofab350.].

Proportion of Pre-Symptomatic Transmission Events Associated with COVID-19 in South Korea

Pre-symptomatic transmission potentially reduces the effectiveness of symptom-onset-based containment and control strategies for the coronavirus disease (COVID-19). Despite evidence from multiple settings, the proportion of pre-symptomatic transmission varies among countries. To estimate the extent of pre-symptomatic transmission in South Korea, we used individual-level COVID-19 case records from the Korea Disease Control and Prevention Agency and Central Disease Control Headquarters. We inferred the probability of symptom onset per day since infection based on the density distribution of the incubation period to stratify the serial interval distribution in Period 1 (20 January–10 February 2020) and Period 2 (25 July–4 December 2021), without and with expanded testing or implementation of social distancing strategies, respectively. Assuming both no correlation as well as positive and negative correlations between the incubation period and the serial interval, we estimated the proportion of pre-symptomatic transmission in South Korea as 43.5% (accounting for correlation, range: 9.9–45.4%) and 60.0% (56.2–64.1%) without and with expanded testing, respectively, during the Delta variant’s predominance. This study highlights the importance of considering pre-symptomatic transmission for COVID-19 containment and mitigation strategies because pre-symptomatic transmission may play a key role in the epidemiology of COVID-19.

Clinical Time Delay Distributions of COVID-19 in 2020-2022 in the Republic of Korea: Inferences from a Nationwide Database Analysis.

Epidemiological distributions of the coronavirus disease 2019 (COVID-19), including the intervals from symptom onset to diagnosis, reporting, or death, are important for developing effective disease-control strategies. COVID-19 case data (from 19 January 2020 to 10 January 2022) from a national database maintained by the Korea Disease Control and Prevention Agency and the Central Disease Control Headquarters were analyzed. A joint Bayesian subnational model with partial pooling was used and yielded probability distribution models of key epidemiological distributions in Korea. Serial intervals from before and during the Delta variant's predominance were estimated. Although the mean symptom-onset-to-report interval was 3.2 days at the national level, it varied across different regions (2.9-4.0 days). Gamma distribution showed the best fit for the onset-to-death interval (with heterogeneity in age, sex, and comorbidities) and the reporting-to-death interval. Log-normal distribution was optimal for ascertaining the onset-to-diagnosis and onset-to-report intervals. Serial interval (days) was shorter before the Delta variant-induced outbreaks than during the Delta variant's predominance (4.4 vs. 5.2 days), indicating the higher transmission potential of the Delta variant. The identified heterogeneity in region-, age-, sex-, and period-based distributions of the transmission dynamics of COVID-19 will facilitate the development of effective interventions and disease-control strategies.

Transmission Potential of the Omicron Variant of Severe Acute Respiratory Syndrome Coronavirus 2 in South Korea, 25 November 2021-8 January 2022.

Our study indicates sustained transmission (effective reproduction number, 1.3; serial interval, 4.2 days; regional doubling times, 3.3-11.4 days) of the severe acute respiratory syndrome coronavirus 2 Omicron (B.1.1.529) variant (N = 2351) in South Korea (25 November 2021-8 January 2022), implicating insufficient protection through vaccination and supporting nonpharmaceutical control measures.

Proportion of Pre-Symptomatic Transmission Events Associated with COVID-19 in South Korea.

Pre-symptomatic transmission potentially reduces the effectiveness of symptom-onset-based containment and control strategies for the coronavirus disease (COVID-19). Despite evidence from multiple settings, the proportion of pre-symptomatic transmission varies among countries. To estimate the extent of pre-symptomatic transmission in South Korea, we used individual-level COVID-19 case records from the Korea Disease Control and Prevention Agency and Central Disease Control Headquarters. We inferred the probability of symptom onset per day since infection based on the density distribution of the incubation period to stratify the serial interval distribution in Period 1 (20 January-10 February 2020) and Period 2 (25 July-4 December 2021), without and with expanded testing or implementation of social distancing strategies, respectively. Assuming both no correlation as well as positive and negative correlations between the incubation period and the serial interval, we estimated the proportion of pre-symptomatic transmission in South Korea as 43.5% (accounting for correlation, range: 9.9-45.4%) and 60.0% (56.2-64.1%) without and with expanded testing, respectively, during the Delta variant's predominance. This study highlights the importance of considering pre-symptomatic transmission for COVID-19 containment and mitigation strategies because pre-symptomatic transmission may play a key role in the epidemiology of COVID-19.

Transmission potential of the Omicron variant of SARS-CoV-2 in South Korea: From November 25, 2020 to January 8, 2022

Our study indicates sustained transmission (effective reproduction number 1.3;serial interval 4.2 days;regional doubling times 3.3–11.4 days) of the severe acute respiratory syndrome coronavirus 2 Omicron (B.1.1.529) variant (n = 2351) in South Korea (November 25, 2021–January 8, 2022), implicating insufficient protection through vaccination and supporting non-pharmaceutical control measures.

An investigation of spatial-temporal patterns and predictions of the coronavirus 2019 pandemic in Colombia, 2020-2021.

Colombia announced the first case of severe acute respiratory syndrome coronavirus 2 on March 6, 2020. Since then, the country has reported a total of 5,002,387 cases and 127,258 deaths as of October 31, 2021. The aggressive transmission dynamics of SARS-CoV-2 motivate an investigation of COVID-19 at the national and regional levels in Colombia. We utilize the case incidence and mortality data to estimate the transmission potential and generate short-term forecasts of the COVID-19 pandemic to inform the public health policies using previously validated mathematical models. The analysis is augmented by the examination of geographic heterogeneity of COVID-19 at the departmental level along with the investigation of mobility and social media trends. Overall, the national and regional reproduction numbers show sustained disease transmission during the early phase of the pandemic, exhibiting sub-exponential growth dynamics. Whereas the most recent estimates of reproduction number indicate disease containment, with Rt<1.0 as of October 31, 2021. On the forecasting front, the sub-epidemic model performs best at capturing the 30-day ahead COVID-19 trajectory compared to the Richards and generalized logistic growth model. Nevertheless, the spatial variability in the incidence rate patterns across different departments can be grouped into four distinct clusters. As the case incidence surged in July 2020, an increase in mobility patterns was also observed. On the contrary, a spike in the number of tweets indicating the stay-at-home orders was observed in November 2020 when the case incidence had already plateaued, indicating the pandemic fatigue in the country.

Predicting New Daily COVID-19 Cases and Deaths Using Search Engine Query Data in South Korea From 2020 to 2021: Infodemiology Study.

BACKGROUND: Given the ongoing COVID-19 pandemic situation, accurate predictions could greatly help in the health resource management for future waves. However, as a new entity, COVID-19's disease dynamics seemed difficult to predict. External factors, such as internet search data, need to be included in the models to increase their accuracy. However, it remains unclear whether incorporating online search volumes into models leads to better predictive performances for long-term prediction. OBJECTIVE: The aim of this study was to analyze whether search engine query data are important variables that should be included in the models predicting new daily COVID-19 cases and deaths in short- and long-term periods. METHODS: We used country-level case-related data, NAVER search volumes, and mobility data obtained from Google and Apple for the period of January 20, 2020, to July 31, 2021, in South Korea. Data were aggregated into four subsets: 3, 6, 12, and 18 months after the first case was reported. The first 80% of the data in all subsets were used as the training set, and the remaining data served as the test set. Generalized linear models (GLMs) with normal, Poisson, and negative binomial distribution were developed, along with linear regression (LR) models with lasso, adaptive lasso, and elastic net regularization. Root mean square error values were defined as a loss function and were used to assess the performance of the models. All analyses and visualizations were conducted in SAS Studio, which is part of the SAS OnDemand for Academics. RESULTS: GLMs with different types of distribution functions may have been beneficial in predicting new daily COVID-19 cases and deaths in the early stages of the outbreak. Over longer periods, as the distribution of cases and deaths became more normally distributed, LR models with regularization may have outperformed the GLMs. This study also found that models performed better when predicting new daily deaths compared to new daily cases. In addition, an evaluation of feature effects in the models showed that NAVER search volumes were useful variables in predicting new daily COVID-19 cases, particularly in the first 6 months of the outbreak. Searches related to logistical needs, particularly for "thermometer" and "mask strap," showed higher feature effects in that period. For longer prediction periods, NAVER search volumes were still found to constitute an important variable, although with a lower feature effect. This finding suggests that search term use should be considered to maintain the predictive performance of models. CONCLUSIONS: NAVER search volumes were important variables in short- and long-term prediction, with higher feature effects for predicting new daily COVID-19 cases in the first 6 months of the outbreak. Similar results were also found for death predictions.

Temporal Changes in the Risk of Superspreading Events of Coronavirus Disease 2019.

To identify the temporal change in the possible risk of superspreading events, we estimated the overdispersion parameter in 2 different periods of the coronavirus disease 2019 pandemic. We determined that the possible risk of superspreading events was reduced 90% during the second epidemic period in South Korea.

Projecting the Impact of SARS-CoV-2 Variants and the Vaccination Program on the Fourth Wave of the COVID-19 Pandemic in South Korea.

Vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are currently administered in South Korea; however, vaccine supply is limited. Considering constraints in vaccine supply and the emergence of variant strains, we evaluated the impact of coronavirus disease (COVID-19) vaccination program in reducing incidence, ICU hospitalization, and deaths in South Korea. We developed an age-structured model of SARS-CoV-2 transmission parameterized with Korean demographics and age-specific COVID-19 outcomes. Using our model, we analyzed the impact of the COVID-19 vaccination program during the fourth wave of the pandemic in South Korea in reducing disease burden. We projected that the vaccination program can reduce the overall attack rate to 3.9% from 6.9% without vaccination, over 150 days, starting from 5 July 2021. The highest relative reduction (50%) was observed among individuals aged 50-59 years. Vaccination markedly reduced adverse outcomes, such as ICU hospitalizations and deaths, decreasing them by 45% and 43%, respectively. In the presence of the Delta variant, vaccination is expected to reduce the overall attack rate to 11.9% from 26.9%. Our results indicate that the impact of vaccination can be substantially affected by the emergence of SARS-CoV-2 variants. Furthermore, herd immunity is unlikely to be achieved with the potential emergence of the Delta variant, inconsistent with the blueprint of the South Korean government.

Vaccine Effects on Susceptibility and Symptomatology Can Change the Optimal Allocation of COVID-19 Vaccines: South Korea as an Example.

The approved coronavirus disease (COVID-19) vaccines reduce the risk of disease by 70-95%; however, their efficacy in preventing COVID-19 is unclear. Moreover, the limited vaccine supply raises questions on how they can be used effectively. To examine the optimal allocation of COVID-19 vaccines in South Korea, we constructed an age-structured mathematical model, calibrated using country-specific demographic and epidemiological data. The optimal control problem was formulated with the aim of finding time-dependent age-specific optimal vaccination strategies to minimize costs related to COVID-19 infections and vaccination, considering a limited vaccine supply and various vaccine effects on susceptibility and symptomatology. Our results suggest that "susceptibility-reducing" vaccines should be relatively evenly distributed among all age groups, resulting in more than 40% of eligible age groups being vaccinated. In contrast, "symptom-reducing" vaccines should be administered mainly to individuals aged 20-29 and ≥60 years. Thus, our study suggests that the vaccine profile should determine the optimal vaccination strategy. Our findings highlight the importance of understanding vaccine's effects on susceptibility and symptomatology for effective public health interventions.

Delay-Adjusted Age-Specific COVID-19 Case Fatality Rates in a High Testing Setting: South Korea, February 2020 to February 2021.

In South Korea, a country with a high coronavirus disease 19 (COVID-19) testing rate, a total of 87,324 COVID-19 cases, including 1562 deaths, have been recorded as of 23 February 2021. This study assessed the delay-adjusted COVID-19 case fatality risk (CFR), including data from the second and third waves. A statistical method was applied to the data from 20 February 2021 through 23 February 2021 to minimize bias in the crude CFR, accounting for the survival interval as the lag time between disease onset and death. The resulting overall delay-adjusted CFR was 1.97% (95% credible interval: 1.94-2.00%). The delay-adjusted CFR was highest among adults aged ≥80 years and 70-79 years (22.88% and 7.09%, respectively). The cumulative incidence rate was highest among individuals aged ≥80 years and 60-69 years. The cumulative mortality rate was highest among individuals aged ≥80 years and 70-79 years (47 and 12 per million, respectively). In South Korea, older adults are being disproportionately affected by COVID-19 with a high death rate, although the incidence rate among younger individuals is relatively high. Interventions to prevent COVID-19 should target older adults to minimize the number of deaths.

Regional Variability in COVID-19 Case Fatality Rate in Canada, February-December 2020.

A total of 475,214 COVID-19 cases, including 13,659 deaths, had been recorded in Canada as of 15 December 2020. The daily reports of confirmed cases and deaths in Canada prior to 15 December 2020 were obtained from publicly available sources and used to examine regional variations in case fatality rate (CFR). Based on a factor of underestimation and the duration of time from symptom onset to death, the time-delay adjusted CFR for COVID-19 was estimated in the four most affected provinces (Quebec, Ontario, Alberta, and British Columbia) and nationwide. The model-based adjusted CFR was higher than the crude CFR throughout the pandemic, primarily owing to the incorporation in our estimation of the delay between case reports and deaths. The adjusted CFR in Canada was estimated to be 3.36% nationwide. At the provincial level, the adjusted CFR was the highest in Quebec (5.13%)-where the proportion of deaths among older individuals was also the highest among the four provinces-followed by Ontario (3.17%), British Columbia (1.97%), and Alberta (1.13%). Provincial-level variations in CFR were considerable, suggesting that public health interventions focused on densely populated areas and elderly individuals can ameliorate the mortality burden of the COVID-19 pandemic.

Optimal Allocation of the Limited COVID-19 Vaccine Supply in South Korea.

Initial supply of the coronavirus disease (COVID-19) vaccine may be limited, necessitating its effective use. Herein, an age-structured model of COVID-19 spread in South Korea is parameterized to understand the epidemiological characteristics of COVID-19. The model determines optimal vaccine allocation for minimizing infections, deaths, and years of life lost while accounting for population factors, such as country-specific age distribution and contact structure, and various levels of vaccine efficacy. A transmission-blocking vaccine should be prioritized in adults aged 20-49 years and those older than 50 years to minimize the cumulative incidence and mortality, respectively. A strategy to minimize years of life lost involves the vaccination of adults aged 40-69 years, reflecting the relatively high case-fatality rates and years of life lost in this age group. An incidence-minimizing vaccination strategy is highly sensitive to vaccine efficacy, and vaccines with lower efficacy should be administered to teenagers and adults aged 50-59 years. Consideration of age-specific contact rates and vaccine efficacy is critical to optimize vaccine allocation. New recommendations for COVID-19 vaccines under consideration by the Korean Centers for Disease Control and Prevention are mainly based on a mortality-minimizing allocation strategy.

Spatial variability in reproduction number and doubling time across two waves of the COVID-19 pandemic in South Korea, February to July, 2020.

OBJECTIVES: In South Korea, 13 745 cases of coronavirus disease (COVID-19) had been reported as of 19 July, 2020. To examine spatiotemporal changes in the transmission potential, we aimed to present regional estimates of the doubling time and reproduction number (Rt) for COVID-19 in the country. METHODS: Daily series of confirmed COVID-19 cases in the most affected regions were extracted from publicly available sources. We employed established mathematical and statistical methods to investigate the time-varying reproduction numbers and doubling time for COVID-19 in Korea. RESULTS: At the regional level, Seoul and Gyeonggi Province experienced the first peak of COVID-19 in early March, followed by a second wave in early June, withRt exceeding 3.0 and mean doubling time ranging from 3.6 to 10.1 days. As of 19 July, 2020, Gyeongbuk Province and Daegu had yet to experience a second wave of the disease. During the first wave, mean Rt for these areas reached 3.5-4.4, and doubling time ranged from 2.8 to 4.6 days. CONCLUSIONS: Our findings support the effectiveness of control measures against COVID-19 in Korea. However, the easing of restrictions that had been imposed by the government in May 2020 facilitated a second wave in the greater Seoul area.

Optimal strategies for social distancing and testing to control COVID-19.

The coronavirus disease (COVID-19) has infected more than 79 million individuals, with 1.7 million deaths worldwide. Several countries have implemented social distancing and testing policies with contact tracing as a measure to flatten the curve of the ongoing pandemic. Optimizing these control measures is urgent given the substantial societal and economic impacts associated with infection and interventions. To determine the optimal social distancing and testing strategies, we developed a mathematical model of COVID-19 transmission and applied optimal control theory, identifying the best approach to reduce the epidemiological burden of COVID-19 at a minimal cost. The results demonstrate that testing as a standalone optimal strategy does not have a significant effect on the final size of an epidemic, but it would delay the peak of the pandemic. If social distancing is the sole control strategy, it would be optimal to gradually increase the level of social distancing as the incidence curve of COVID-19 grows, and relax the measures after the curve has reached its peak. Compared with a single strategy, combined social distancing and testing strategies are demonstrated to be more efficient at reducing the disease burden, and they can delay the peak of the disease. To optimize these strategies, testing should be maintained at a maximum level in the early phases and after the peak of the epidemic, whereas social distancing should be intensified when the prevalence of the disease is greater than 15%. Accordingly, public health agencies should implement early testing and switch to social distancing when the incidence level begins to increase. After the peak of the pandemic, it would be optimal to gradually relax social distancing and switch back to testing.

Understanding the Community Risk Perceptions of the COVID-19 Outbreak in South Korea: Infodemiology Study.

BACKGROUND: South Korea is among the best-performing countries in tackling the coronavirus pandemic by using mass drive-through testing, face mask use, and extensive social distancing. However, understanding the patterns of risk perception could also facilitate effective risk communication to minimize the impacts of disease spread during this crisis. OBJECTIVE: We attempt to explore patterns of community health risk perceptions of COVID-19 in South Korea using internet search data. METHODS: Google Trends (GT) and NAVER relative search volumes (RSVs) data were collected using COVID-19-related terms in the Korean language and were retrieved according to time, gender, age groups, types of device, and location. Online queries were compared to the number of daily new COVID-19 cases and tests reported in the Kaggle open-access data set for the time period of December 5, 2019, to May 31, 2020. Time-lag correlations calculated by Spearman rank correlation coefficients were employed to assess whether correlations between new COVID-19 cases and internet searches were affected by time. We also constructed a prediction model of new COVID-19 cases using the number of COVID-19 cases, tests, and GT and NAVER RSVs in lag periods (of 1-3 days). Single and multiple regressions were employed using backward elimination and a variance inflation factor of <5. RESULTS: The numbers of COVID-19-related queries in South Korea increased during local events including local transmission, approval of coronavirus test kits, implementation of coronavirus drive-through tests, a face mask shortage, and a widespread campaign for social distancing as well as during international events such as the announcement of a Public Health Emergency of International Concern by the World Health Organization. Online queries were also stronger in women (r=0.763-0.823; P<.001) and age groups ≤29 years (r=0.726-0.821; P<.001), 30-44 years (r=0.701-0.826; P<.001), and ≥50 years (r=0.706-0.725; P<.001). In terms of spatial distribution, internet search data were higher in affected areas. Moreover, greater correlations were found in mobile searches (r=0.704-0.804; P<.001) compared to those of desktop searches (r=0.705-0.717; P<.001), indicating changing behaviors in searching for online health information during the outbreak. These varied internet searches related to COVID-19 represented community health risk perceptions. In addition, as a country with a high number of coronavirus tests, results showed that adults perceived coronavirus test-related information as being more important than disease-related knowledge. Meanwhile, younger, and older age groups had different perceptions. Moreover, NAVER RSVs can potentially be used for health risk perception assessments and disease predictions. Adding COVID-19-related searches provided by NAVER could increase the performance of the model compared to that of the COVID-19 case-based model and potentially be used to predict epidemic curves. CONCLUSIONS: The use of both GT and NAVER RSVs to explore patterns of community health risk perceptions could be beneficial for targeting risk communication from several perspectives, including time, population characteristics, and location.

Optimal strategies for vaccination and social distancing in a game-theoretic epidemiologic model.

For various infectious diseases, vaccination has become a major intervention strategy. However, the importance of social distancing has recently been highlighted during the ongoing COVID-19 pandemic. In the absence of vaccination, or when vaccine efficacy is poor, social distancing may help to curb the spread of new virus strains. However, both vaccination and social distancing are associated with various costs. It is critical to consider these costs in addition to the benefits of these strategies when determining the optimal rates of application of control strategies. We developed a game-theoretic epidemiological model that considers vaccination and social distancing under the assumption that individuals pursue the maximization of payoffs. By using this model, we identified the individually optimal strategy based on the Nash strategy when both strategies are available and when only one strategy is available. Furthermore, we determined the relative costs of control strategies at which individuals preferentially adopt vaccination over social distancing (or vice versa).

Estimating the Risk of COVID-19 Death During the Course of the Outbreak in Korea, February-May 2020.

BACKGROUND: In Korea, a total of 10,840 confirmed cases of COVID-19 including 256 deaths have been recorded as of May 9, 2020. The time-delay adjusted case fatality risk (CFR) of COVID-19 in Korea is yet to be estimated. METHODS: We obtained the daily series of confirmed cases and deaths in Korea reported prior to May 9, 2020. Using statistical methods, we estimated the time-delay adjusted risk for death from COVID-19 in Daegu, Gyeongsangbuk-do, other regions in Korea, as well as the entire country. RESULTS: Our model-based crude CFR fitted the observed data well throughout the course of the epidemic except for the very early stage in Gyeongsangbuk-do; this was partially due to the reporting delay. Our estimates of the risk of death in Gyeongsangbuk-do reached 25.9% (95% Credible Interval (CrI): 19.6%-33.6%), 20.8% (95% CrI: 18.1%-24.0%) in Daegu, and 1.7% (95% CrI: 1.1%-2.5%) in other regions, whereas the national estimate was 10.2% (95% CrI: 9.0%-11.5%). CONCLUSIONS: The latest estimates of CFR of COVID-19 in Korea are considerably high, even with the early implementation of public health interventions including widespread testing, social distancing, and delayed school openings. Geographic differences in the CFR are likely influenced by clusters tied to hospitals and nursing homes.

Transmission potential and severity of COVID-19 in South Korea.

OBJECTIVES: Since the first case of 2019 novel coronavirus (COVID-19) identified on Jan 20, 2020, in South Korea, the number of cases rapidly increased, resulting in 6284 cases including 42 deaths as of Mar 6, 2020. To examine the growth rate of the outbreak, we present the first study to report the reproduction number of COVID-19 in South Korea. METHODS: The daily confirmed cases of COVID-19 in South Korea were extracted from publicly available sources. By using the empirical reporting delay distribution and simulating the generalized growth model, we estimated the effective reproduction number based on the discretized probability distribution of the generation interval. RESULTS: We identified four major clusters and estimated the reproduction number at 1.5 (95% CI: 1.4-1.6). In addition, the intrinsic growth rate was estimated at 0.6 (95% CI: 0.6, 0.7), and the scaling of growth parameter was estimated at 0.8 (95% CI: 0.7, 0.8), indicating sub-exponential growth dynamics of COVID-19. The crude case fatality rate is higher among males (1.1%) compared to females (0.4%) and increases with older age. CONCLUSIONS: Our results indicate an early sustained transmission of COVID-19 in South Korea and support the implementation of social distancing measures to rapidly control the outbreak.