National Infectious Diseases Surveillance data of South Korea.
ABSTRACT: The Korea Centers for Disease Control and Prevention (KCDC) operate infectious disease surveillance systems to monitor national disease incidence. Since 1954, Korea has collected data on various infectious diseases in accordance with the Infectious Disease Control and Prevention Act. All physicians (including those working in Oriental medicine) who diagnose a patient with an infectious disease or conduct a postmortem examination of an infectious disease case are obliged to report the disease to the system. These reported data are incorporated into the database of the National Infectious Disease Surveillance System, which has been providing web-based real-time surveillance data on infectious diseases since 2001. In addition, the KCDC analyzes reported data and publishes the Infectious Disease Surveillance Yearbook annually.
Project description:OBJECTIVES:While the seasonality of notified tuberculosis has been identified in several populations, there is not a descriptive epidemiological study on the seasonality of tuberculosis in Korea. This study aimed to evaluate the seasonality of tuberculosis in Korea from 2006 to 2016. METHODS:Data regarding notified cases of tuberculosis by year and month was obtained from the Infectious Diseases Surveillance Yearbook, 2017 published by the Korea Centers for Disease Control and Prevention. Seasonal decomposition was conducted using the method of structural model of time series analysis with simple moving averages. RESULTS:While the trough season was winter from 2006 to 2016, the peak season was summer between 2006 and 2012, but shifted to spring between 2013 and 2016. CONCLUSIONS:Notified tuberculosis in Korea also showed seasonality. It is necessary to evaluate factors related to the seasonality of tuberculosis for controlling tuberculosis.
Project description:<h4>Background</h4>Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease that was recently identified in China, South Korea and Japan. The objective of the study was to evaluate the epidemiologic and clinical characteristics of SFTS in South Korea.<h4>Methods/principal findings</h4>SFTS is a reportable disease in South Korea. We included all SFTS cases reported to the Korea Centers for Disease Control and Prevention (KCDC) from January 2013 to December 2015. Clinical information was gathered by reviewing medical records, and epidemiologic characteristics were analyzed using both KCDC surveillance data and patient medical records. Risk factors for mortality in patients with SFTS were assessed. A total of 172 SFTS cases were reported during the study period. SFTS occurred throughout the country, except in urban areas. Hilly areas in the eastern and southeastern regions and Jeju island (incidence, 1.26 cases /105 person-years) were the main endemic areas. The yearly incidence increased from 36 cases in 2013 to 81 cases in 2015. Most cases occurred from May to October. The overall case fatality ratio was 32.6%. The clinical progression was similar to the 3 phases reported in China: fever, multi-organ dysfunction, and convalescence. Confusion, elevated C-reactive protein, and prolonged activated partial thromboplastin times were associated with mortality in patients with SFTS. Two outbreaks of nosocomial SFTS transmission were observed.<h4>Conclusions</h4>SFTS is an endemic disease in South Korea, with a nationwide distribution and a high case-fatality ratio. Confusion, elevated levels of C-reactive protein, and prolonged activated partial thromboplastin times were associated with mortality in patients with SFTS.
Project description:The Korea National Health and Nutrition Examination Survey (KNHANES) is a national surveillance system that has been assessing the health and nutritional status of Koreans since 1998. Based on the National Health Promotion Act, the surveys have been conducted by the Korea Centers for Disease Control and Prevention (KCDC). This nationally representative cross-sectional survey includes approximately 10 000 individuals each year as a survey sample and collects information on socioeconomic status, health-related behaviours, quality of life, healthcare utilization, anthropometric measures, biochemical and clinical profiles for non-communicable diseases and dietary intakes with three component surveys: health interview, health examination and nutrition survey. The health interview and health examination are conducted by trained staff members, including physicians, medical technicians and health interviewers, at a mobile examination centre, and dieticians' visits to the homes of the study participants are followed up. KNHANES provides statistics for health-related policies in Korea, which also serve as the research infrastructure for studies on risk factors and diseases by supporting over 500 publications. KCDC has also supported researchers in Korea by providing annual workshops for data users. KCDC has published the Korea Health Statistics each year, and microdata are publicly available through the KNHANES website (http://knhanes.cdc.go.kr).
Project description:We used a survey about the need for an educational training of infectious disease response staff in Korea Centers for Disease Control and Prevention (KCDC) and officer in metropolitan cities and provincial government to conduct field epidemiological investigation. The survey was conducted from January 25 to March 15, 2016. A total of 173 participants were selected from four different groups as follows: 27 clinical specialists, 22 Epidemic Intelligence Service (EIS) officers, 82 KCDC staff, and 42 local health department officials. Results revealed that 83% of KCDC staff and 95% of local health department officials agreed on the need for educational training to strengthen capability of personnel to conduct epidemic research and investigation. The level of their need for training was relatively high, while self-confidence levels of individuals to conduct epidemic research and investigation was low. It was concluded that there was a need to develop training programs to enhance the ability of public health officials, EIS officers, KCDC staff, and local health department personnel to conduct epidemic research and investigation.
Project description:BACKGROUND:Effective surveillance of influenza requires a broad network of health care providers actively reporting cases of influenza-like illnesses and positive laboratory results. Not only is this traditional surveillance system costly to establish and maintain but there is also a time lag between a change in influenza activity and its detection. A new surveillance system that is both reliable and timely will help public health officials to effectively control an epidemic and mitigate the burden of the disease. OBJECTIVE:This study aimed to evaluate the use of parent-reported data of febrile illnesses in children submitted through the Fever Coach app in real-time surveillance of influenza activities. METHODS:Fever Coach is a mobile app designed to help parents and caregivers manage fever in young children, currently mainly serviced in South Korea. The app analyzes data entered by a caregiver and provides tailored information for care of the child based on the child's age, sex, body weight, body temperature, and accompanying symptoms. Using the data submitted to the app during the 2016-2017 influenza season, we built a regression model that monitors influenza incidence for the 2017-2018 season and validated the model by comparing the predictions with the public influenza surveillance data from the Korea Centers for Disease Control and Prevention (KCDC). RESULTS:During the 2-year study period, 70,203 diagnosis data, including 7702 influenza reports, were submitted. There was a significant correlation between the influenza activity predicted by Fever Coach and that reported by KCDC (Spearman ?=0.878; P<.001). Using this model, the influenza epidemic in the 2017-2018 season was detected 10 days before the epidemic alert announced by KCDC. CONCLUSIONS:The Fever Coach app successfully collected data from 7.73% (207,699/2,686,580) of the target population by providing care instruction for febrile children. These data were used to develop a model that accurately estimated influenza activity measured by the central government agency using reports from sentinel facilities in the national surveillance network.
Project description:Infectious disease occurs when a person is infected by a pathogen from another person or an animal. It is a problem that causes harm at both individual and macro scales. The Korea Center for Disease Control (KCDC) operates a surveillance system to minimize infectious disease contagions. However, in this system, it is difficult to immediately act against infectious disease because of missing and delayed reports. Moreover, infectious disease trends are not known, which means prediction is not easy. This study predicts infectious diseases by optimizing the parameters of deep learning algorithms while considering big data including social media data. The performance of the deep neural network (DNN) and long-short term memory (LSTM) learning models were compared with the autoregressive integrated moving average (ARIMA) when predicting three infectious diseases one week into the future. The results show that the DNN and LSTM models perform better than ARIMA. When predicting chickenpox, the top-10 DNN and LSTM models improved average performance by 24% and 19%, respectively. The DNN model performed stably and the LSTM model was more accurate when infectious disease was spreading. We believe that this study's models can help eliminate reporting delays in existing surveillance systems and, therefore, minimize costs to society.
Project description:<h4>Background</h4>Scrub typhus is a mite-borne infectious disease caused by Orientia tsutsugamushi. Few follow-up studies have assessed antibody titers using serologic tests from various commercial laboratories and the Korea Centers for Disease Control and Prevention (KCDC).<h4>Methods</h4>A prospective study to assess the antibody titers in patients with scrub typhus and seroprevalence in individuals undergoing health checkups was conducted using results of immunofluorescence antibody assays (IFAs) and serologic tests, used by the KCDC and commercial laboratories, respectively. The following tests were performed simultaneously: (i) indirect IFA used by the KCDC to detect immunoglobulin (Ig) M and IgG, (ii) IFA used by a commercial laboratory to detect total Ig, and (iii) antibody tests using two commercially available kits.<h4>Results</h4>When the IgM and IgG cutoff values (?1:16 and ?1:256, respectively) used in the IFA and the total IgG cutoff values (?1:40) were used in prospective follow-up investigations, the antibody positivity rates of 102 patients with scrub typhus were 44.1, 35.3, and 57.6%, respectively, within 5?days of symptom onset. Among 91 individuals who recovered from scrub typhus, the follow-up IgM, IgG, and total Ig positivity rates for 13?years were 37.4% (34/91), 22.0% (20/91), and 76.9% (70/91), respectively. Among 216 individuals undergoing health checkups, the seroprevalence of IgM was 4.2% (9/216); no seroprevalence of IgG was observed.<h4>Conclusions</h4>IFAs used by the KCDC and the commercial laboratory and rapid commercial kits could not distinguish between patients who had recovered from scrub typhus and those who are currently infected with O. tsutsugamushi. In South Korea and other countries, where low antibody cutoff values are used, upward adjustments of cutoff values may be necessary.
Project description:The general elections for the 21st National Assembly in the Republic of Korea were scheduled for April 15th, 2020, which was during the novel coronavirus disease (COVID-19) outbreak. To ensure a safe election, the Korean Centers for Disease Control and Prevention (KCDC) recommended several public health measures. The KCDC developed key interventions after reviewing the general election strategy that targeted COVID-19 patients and individuals isolating at home. Four voters who participated in the election tested positive, but did not contract COVID-19 during voting. The results demonstrated that the KCDC minimized the spread of infection in the community during the election. The measures implemented by KCDC during the election held under a COVID-19 outbreak cannot be generalized to elections as a whole because cultural and national consciousness vary between countries. Nevertheless, it demonstrates that the systemic strategies and applications against the pandemic can minimize the possibility of viral spread.
Project description:Early detection of infectious disease outbreaks is one of the important and significant issues in syndromic surveillance systems. It helps to provide a rapid epidemiological response and reduce morbidity and mortality. In order to upgrade the current system at the Korea Centers for Disease Control and Prevention (KCDC), a comparative study of state-of-the-art techniques is required. We compared four different temporal outbreak detection algorithms: the CUmulative SUM (CUSUM), the Early Aberration Reporting System (EARS), the autoregressive integrated moving average (ARIMA), and the Holt-Winters algorithm. The comparison was performed based on not only 42 different time series generated taking into account trends, seasonality, and randomly occurring outbreaks, but also real-world daily and weekly data related to diarrhea infection. The algorithms were evaluated using different metrics. These were namely, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), F1 score, symmetric mean absolute percent error (sMAPE), root-mean-square error (RMSE), and mean absolute deviation (MAD). Although the comparison results showed better performance for the EARS C3 method with respect to the other algorithms, despite the characteristics of the underlying time series data, Holt?Winters showed better performance when the baseline frequency and the dispersion parameter values were both less than 1.5 and 2, respectively.
Project description:The Korea Centers for Diseases Control and Prevention (KCDC) has announced a control program against latent <i>Mycobacterium tuberculosis</i> infection (LTBI), for a "TB-safe country" this year with the goal of a "TB-free Korea" by 2025. The program includes high school students as one target group; however, some school health teachers and parents have expressed their opposition to this. The 2015 World Health Organization guidelines do not recommend inclusion of asymptomatic high school students in LTBI control programs. Based on this guideline, the KCDC should consider excluding this population from the program.