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Evidence regarding the effectiveness of contact tracing of COVID-19 and the related social distancing is limited and inconclusive.
This study aims to investigate the epidemiological characteristics of SARS-CoV-2 transmission in South Korea and evaluate whether a social distancing campaign is effective in mitigating the spread of COVID-19.
We used contract tracing data to investigate the epidemic characteristics of SARS-CoV-2 transmission in South Korea and evaluate whether a social distancing campaign was effective in mitigating the spread of COVID-19. We calculated the mortality rate for COVID-19 by infection type (cluster vs noncluster) and tested whether new confirmed COVID-19 trends changed after a social distancing campaign.
There were 2537 patients with confirmed COVID-19 who completed the epidemiologic survey: 1305 (51.4%) cluster cases and 1232 (48.6%) noncluster cases. The mortality rate was significantly higher in cluster cases linked to medical facilities (11/143, 7.70% vs 5/1232, 0.41%; adjusted percentage difference 7.99%; 95% CI 5.83 to 10.14) and long-term care facilities (19/221, 8.60% vs 5/1232, 0.41%; adjusted percentage difference 7.56%; 95% CI 5.66 to 9.47) than in noncluster cases. The change in trends of newly confirmed COVID-19 cases before and after the social distancing campaign was significantly negative in the entire cohort (adjusted trend difference –2.28; 95% CI –3.88 to –0.68) and the cluster infection group (adjusted trend difference –0.96; 95% CI –1.83 to –0.09).
In a nationwide contact tracing study in South Korea, COVID-19 linked to medical and long-term care facilities significantly increased the risk of mortality compared to noncluster COVID-19. A social distancing campaign decreased the spread of COVID-19 in South Korea and differentially affected cluster infections of SARS-CoV-2.
The novel coronavirus that emerged in Wuhan, China, termed SARS-CoV-2, has caused a rapidly spreading outbreak of COVID-19 worldwide [
The democratic republic of South Korea, one of the geographical neighbors of China, had the second highest number of COVID-19 cases until February 2020 [
Based on the experience with the Middle East respiratory syndrome (MERS) outbreak, South Korea has set up a novel monitoring system to collect information and manage patients with COVID-19 and their contacts by using GPD (cell phone location), card transaction logs, closed-circuit television (CCTV), and a history of medical facility use [
Data were collected from individuals with laboratory-confirmed SARS-CoV-2 infection who subsequently completed the preliminary epidemiological surveillance conducted by each local government of South Korea (Seoul, Incheon, Sejong, Daegu, Gwangju, Ulsan, Busan, Gyeonggi-do, Gangwon-do, Chungcheongbuk-do [Chungbuk], Chungcheongnam-do [Chungnam], Gyeongsangbuk-do [Gyeongbuk], Gyeongsangnam-do [Gyeongnam], Jeollabuk-do [Jeonbuk], Jeollanam-do [Jeonnam], and Jeju) [
A cluster infection was defined as a group of similar COVID-19 cases that occurred in the same area during a short time interval. Nonclustered cases were patients with COVID-19 unrelated to any other patients with COVID-19 in time or place [
We set January 19, 2020, as the index date (epidemiologic day 1) and April 7, 2020, as epidemiologic day 80. The primary endpoint was the mortality risk among participants with noncluster infection and those with cluster infection. Analysis of covariance was used to calculate the adjusted mean difference and 95% CI after adjustment. The following factors were considered potential confounders: age (0-19 years, 20-39 years, 40-59 years, and 60 years or older), sex, diagnosis date, and region of residence (urban [Seoul, Incheon, Sejong, Daegu, Gwangju, Ulsan, and Busan] vs rural [Gyeonggi-do, Gangwon-do, Chungbuk, Chungnam, Gyeongbuk, Gyeongnam, Jeonbuk, Jeonnam, and Jeju]).
Our secondary endpoint was whether a social distancing campaign was effective in mitigating the spread of COVID-19. We divided the population into two distinct periods: before the social distancing campaign (January 19, 2020, to March 22, 2020) and after the social distancing campaign (March 23, 2020, to April 7, 2020). We tested whether trends in newly confirmed COVID-19 cases changed after the social distancing campaign compared with those before the campaign. We implemented interrupted time series analysis to detect a change of slope after the launch of the nationwide social distancing campaign. We introduced the following equation to compare the effect of the campaign, where:
Yt is the newly infected person on day t; T is the number of days elapsed from the first confirmed infectious case;
Network visualization was performed using Gephi version 0.9.2 [
Each categorical value is reported as the number of patients (percentage). Statistical analyses were performed using SPSS version 25.0 (IBM Corp), and R software version 3.6.2 (R Foundation for Statistical Computing). A two-sided
No patients were directly involved in designing the research question or conducting the research. No patients were asked to interpret or write up the results. There are no plans to involve patients or relevant patient communities in dissemination at this moment.
From January 19, 2020, to April 7, 2020, there were 10,046 patients with laboratory-confirmed COVID-19 in South Korea. Among the 10,046 patients, 7509 were excluded for the following reasons: epidemiological investigation was not possible due to community-level outbreaks (Daegu and two cities in Gyeongbuk [Cheongdo and Gyeongsan]; n=7493) or because the epidemiological investigation was incomplete (n=16). The final sample size was 2537 (1160 men and 1377 women;
Our study population in each region (number of our study population/number of total patients with confirmed COVID-19). Of 9550 patients with confirmed COVID-19, there were 2134 patients with confirmed COVID-19 who completed the epidemiological surveillance.
Demographic characteristics of patients with confirmed COVID-19 in South Korea.
Characteristic | Entire cohort, n (%) | Cluster and contact cases, n (%) | Noncluster casesa, n (%) | |||||
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Linked to medical facilities | Linked to long-term care facilities | Linked to religious facilities | Othersb |
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Patients | 2537 (100) | 143 (5.6) | 221 (8.7) | 486 (19.2) | 455 (17.9) | 1232 (48.6) | ||
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0-19 | 151 (6.0) | 3 (2.1) | 2 (0.9) | 33 (6.8) | 35 (7.7) | 78 (6.3) | |
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20-39 | 974 (38.4) | 28 (19.6) | 15 (6.8) | 196 (40.3) | 123 (27.0) | 612 (49.7) | |
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40-59 | 805 (31.7) | 44 (30.8) | 39 (17.6) | 162 (33.3) | 240 (52.7) | 320 (26.0) | |
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≥60 | 607 (23.9) | 68 (47.6) | 165 (74.7) | 95 (19.5) | 57 (12.5) | 222 (18.0) | |
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Male | 1160 (45.7) | 49 (34.3) | 68 (30.8) | 228 (46.9) | 176 (38.7) | 639 (51.9) | |
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Female | 1377 (54.3) | 94 (65.7) | 153 (69.2) | 258 (53.1) | 279 (61.3) | 593 (48.1) | |
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Urban | 934 (36.8) | 25 (17.5) | 8 (3.6) | 146 (30.0) | 210 (46.2) | 545 (44.2) | |
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Rural | 1603 (63.2) | 118 (82.5) | 213 (96.4) | 340 (70.0) | 245 (53.8) | 687 (55.8) | |
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No | 2500 (98.5) | 132 (92.3) | 202 (91.4) | 485 (99.8) | 454 (99.8) | 1227 (99.6) | |
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Yes | 37 (1.5) | 11 (7.7) | 19 (8.6) | 1 (0.2) | 1 (0.2) | 5 (0.4) |
aNoncluster cases were linked to overseas influx (641/2537, 25.3%), influx for community-infection outbreak areas (229/2537, 9.0%), and sporadic cases (362/2537, 14.3%).
bOther facilities included military units, dance studios, karaoke, internet cafés, public transport, prisons, and workplaces of each patient.
Number of infections based on infection type (cluster and contact cases vs noncluster cases) in South Korea from January 19, 2020, to April 7, 2020.
Infection spread network visualization of COVID-19 in South Korea from January 19, 2020, to April 7, 2020. Each dot represents an individual, and each line represents an individual’s tracing results. Overseas influx and influx of community-acquired infections (Daegu and two cities in Gyeongbuk [Cheongdo and Gyeongsan]) are shown by 641 and 229 connected dots, respectively. CA: community-acquired.
Mortality rate for COVID-19 according to the infection route in South Korea (n=2134).a
Cases | Mortality percentage (95% CI) | Adjusted difference (95% CI) | |||||
Noncluster cases | 0.41 (–0.25 to 1.06) | Reference |
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Linked to medical facilities | 7.70 (5.78 to 9.61) | 7.99 (5.83 to 10.14) | <.001 | |||
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Linked to long-term care facilities | 8.60 (7.06 to 10.14) | 7.56 (5.66 to 9.47) | <.001 | |||
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Linked to religious facilities | 0.21 (–0.83 to 1.24) | –0.14 (–1.40 to 1.13) | .88 | |||
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Others | 0.22 (–0.85 to 1.29) | –0.14 (–1.42 to 1.15) | .88 |
aRisk factors were adjusted by age (0-19 years, 20-39 years, 40-59 years, and 60 years or older), sex, diagnosis date, and region of residence (urban [Seoul, Incheon, Sejong, Daegu, Gwangju, Ulsan, and Busan] vs rural [Gyeonggi-do, Gangwon-do, Chungbuk, Chungnam, Gyeongbuk, Gyeongnam, Jeonbuk, Jeonnam, and Jeju]).
New confirmed COVID-19 cases trends before and after a social distancing campaign in South Korea.a
Groups | Trend before the social distancing campaign (95% CI) | Trend after the social distancing campaign (95% CI) | Trend difference (95% CI) | |
Overall | 1.11 (0.62 to 1.59) | –1.18 (–2.70 to 0.34) | –2.28 (–3.88 to –0.68) | .005 |
Cluster | 0.43 (–0.10 to 0.96) | –0.53 (–1.22 to 0.17) | –0.96 (–1.83 to –0.09) | .03 |
Noncluster | 0.35 (0.16 to 0.54) | –0.34 (–1.34 to 0.67) | –0.69 (–1.71 to 0.33) | .19 |
aRisk factors were adjusted by age, sex, and region of residence.
Number of new confirmed COVID-19 cases over the study period. The dashed vertical line at March 22, 2020, indicates the launch of the social distancing campaign. The solid red (before the social distancing campaign) and blue (after the social distancing campaign) lines represent the linear trends of new confirmed COVID-19 cases. Shaded areas represent 95% CIs for the linear trends.
To our knowledge, this is the first study to investigate the results of nationwide contact tracing of patients with COVID-19 and examine whether a social distancing campaign is effective in mitigating the spread of COVID-19. Cases of cluster infection and their contacts, which accounted for 51.4% (1305/2537) of the cases in this study, were linked to medical facilities, long-term care facilities, religious facilities, and other locations (military units, dance studios, karaoke bars, internet cafés, public transport, prisons, and workplaces of each patient). Moreover, COVID-19 linked to medical and long-term care facilities significantly increased the risk of mortality compared to noncluster COVID-19. Our study also showed that the social distancing campaign decreased the spread of COVID-19 in South Korea and differentially affected cluster infections of SARS-CoV-2. Therefore, strategies for the prevention of cluster infection of SARS-CoV-2 should be personalized and comprehensive, and multidisciplinary strategies to prevent COVID-19 should be developed. In particular, special attention should be paid to prevent cluster infections of SARS-CoV-2, especially in medical and long-term care facilities.
The pandemic spread of COVID-19 is exponentially escalating [
An in-depth analysis of clustered cases revealed that a higher proportion of confirmed COVID-19 cases were related to religious, long-term care, and medical facilities. Cases from medical and long-term care facilities had a high mortality rate (11/143, 7.70% and 19/221, 8.60%, respectively) due to a higher proportion of vulnerable people including older adults and patients who are chronically ill present among these cases. These facilities are typically crowded with people in enclosed rooms, which create favorable conditions for transmission of respiratory diseases [
The enforced social distancing campaign was introduced by the Korean government on March 22, 2020. Our data support the enforced social distancing campaign as a highly effective method for preventing clustered infections. Our analyses demonstrated a significant reduction in clustered SARS-CoV-2 infections (adjusted trend difference –0.96; 95% CI –1.83 to –0.09) after the launch of the nationwide campaign. Since SARS-CoV-2 is transmitted via respiratory droplets [
It is interesting to note that the overseas influx had a significant role in the spread of the virus in South Korea. Recently, many countries have imposed government-issued international travel restrictions [
As the nature of COVID-19 is subclinical in some individuals, isolating early detected confirmed cases before transmission can occur is difficult [
First, as previously mentioned, one of the strengths of our study is that novel individual contact tracing data acquired by the KCDC and each local government in South Korea was used. By tracing individual data, we could categorize the source and characteristics of the transmission. Additionally, most other countries have not performed epidemiological surveys that include contact tracing; South Korea is thus far the only country to conduct epidemiological surveys with contact tracing. Therefore, we were able to identify the spread dynamics of COVID-19. Second, our study has a clear time point when a nationwide social distancing campaign was launched. Therefore, we could compare the trends of transmission before and after the campaign and evaluate the effectiveness of the public health intervention. Nonetheless, our study has some limitations. First, our data did not contain clinical information because we could not link hospital data to the epidemiological survey expeditiously. Second, we are still developing epidemiological surveys that include information on socioeconomic status (personal occupation and income) and time to development of COVID-19–related symptoms; hence, we were unable to analyze the time to symptom onset or socioeconomic status. Third, although the WHO stated that contact tracing includes the process of identifying, assessing, and managing people who have been exposed to a disease to prevent onward transmission [
In this study, we investigated the nationwide contact tracing results of patients with COVID-19 and whether the social distancing campaign was effective in mitigating the spread of COVID-19. COVID-19 linked to medical and long-term care facilities significantly increased the risk of mortality compared with noncluster COVID-19. Moreover, our study shows that the social distancing campaign decreased the spread of COVID-19 in South Korea and differentially affected cluster infections of SARS-CoV-2. Therefore, our data may support driving public health policies in other countries and help normalize and restore social activities while minimizing the risk of transmission. Further cooperative global epidemic studies and updates are warranted to drive the best policy to control the transmission of SARS-CoV-2.
The dynamic infection spread network video of the COVID-19 in South Korea. The bottom bar represents the elapsed day after the first infection has occurred. The video includes the first 80 days of spread. Each line represents the spread occurrence between persons, and each dot represents the infected individual. Larger dots represent clustered infections, with dynamically increasing size, which means the number of infections in that cluster as time proceeds.
closed-circuit television
Korea Centers for Disease Control and Prevention
Middle East respiratory syndrome
severe acute respiratory syndrome
World Health Organization
This work was supported by the Institute of Information and Communications Technology Planning & Evaluation grant funded by the Korea government (MSIT); No.2020-0-00512, Data Refinement and Improvement through Data Quality Evaluation. The funders had no role in the study design, data collection, data analysis, data interpretation, or writing of the report.
DKY had full access to all of the data in the study and took responsibility for the integrity of the data and the accuracy of the data analysis. All authors approved the final version before submission. The study concept and design was done by SWL, WTY, and DKY. Acquisition, analysis, or interpretation of data was done by SWL, WTY, and DKY. Drafting of the manuscript was done by JMY and DKY. Critical revision of the manuscript for important intellectual content was done by Y-SC, IKY, HYK, DM, DO, EKH, MYH, and DKY. Statistical analysis was done by SWL, Y-SC, and DKY. Study supervision was done by DKY. DKY is guarantor. The corresponding author attests that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted.
None declared.