PHWR Public Health Weekly Report

The Korea Disease Control and Prevention Agency (KDCA) has historically operated the Infectious Disease Management System (IDMS) for disease reporting and epidemiological investigations, and the Quarantine Information System (QIS) for quarantine inspections of international arrivals, vessels, and aircrafts. After the onset of the coronavirus disease 2019 (COVID-19) pandemic in 2020, the agency developed the COVID-19 Information Management System (CIMS) to rapidly support evolving public health measures and manage the system load from a surge in confirmed cases. However, these systems operated in silos without interconnectivity, which resulted in duplicated functions, difficulty in information sharing, and reduced efficiency in disease control efforts.

To support swift and efficient disease control operations, the KDCA launched the “Project to Establish the Infectious Disease Information System and Big Data Platform” in November 2022, which integrated the IDMS, QIS, and CIMS and standardized key data from reports and epidemiological investigations. The Infectious Disease Information System was launched in January 2024, followed by the Infectious Disease Big Data Platform in June 2024. The KDCA continues to improve its infectious disease response by automatically generating incidence statistics and supporting customized analyses based on data from the integrated system.

1. Background

COVID-19 spread globally in a short period, establishing itself as one of the most severe public health crises in human history. In its initial response, the Republic of Korea (ROK) faced numerous limitations not only in its infectious disease management framework but also in its information system operations. The previous record for total reported cases of all legally mandated comprehensive surveillance diseases was approximately 160,000 annually (2018). In contrast, daily reports exceeded 620,000 at the peak of the COVID-19 pandemic, rendering the existing systems effectively inoperable. Furthermore, infectious disease data was fragmented across IDMS, QIS, and CIMS. This lack of integration led to repeated delays and errors in information sharing. In particular, critical information for disease response, including reporting, pathogen identification, epidemiological investigation, and patient management, was managed in a fragmented manner, frequently hindering effective decision-making in the field. This highlighted the urgent need for a new information framework to integrally manage data across the entire disease response lifecycle, enabling an effective response to public health crises and informing policy. In response, the KDCA initiated the development of the Infectious Disease Information System, redesigning major public health systems into a single, unified platform to standardize, rapidly process, and share infectious disease information.

2. Analysis of International Cases

In ROK, insufficient system integration was a key issue, disrupting the end-to-end data flow from disease occurrence to response and impeding rapid, field-oriented action. Cases from the United States and Europe that addressed data fragmentation across systems were referenced during the development of the integrated system. The U.S. faced challenges in mounting a rapid, coordinated national response to outbreaks spanning multiple states owing to its structural model of managing infectious disease information at the state level. In response, the U.S. Centers for Disease Control and Prevention (CDC) integrated multiple surveillance systems, including the National Notifiable Diseases Surveillance System, into the National Electronic Disease Surveillance System in the early 2000s. By linking with clinical information systems and automated laboratory reporting, the CDC established an integrated infrastructure that provided accurate, complete, and timely infectious disease data [1,2].

Similarly, since 2003, Europe has progressively integrated its national reporting frameworks, centrally collecting and managing infectious disease data through The European Surveillance System (TESSy), overseen by the European Centre for Disease Prevention and Control. TESSy was introduced to overcome non-standardization issues, such as disparate data collection formats and duplicate reporting among member states. By establishing a “one-stop surveillance system,” it has become the foundation for a joint response to cross-border disease threats [3].

The U.S. addressed state-level fragmentation, Europe tackled national heterogeneity, and ROK focused on resolving process disruptions. Despite these different core challenges, all reached the same instructive conclusion: an integrated system was necessary for data standardization, real-time sharing, and interoperability. ROK thus aimed to substantially strengthen its infectious disease response capabilities by building an integrated information system to connect and manage the entire process from outbreak to response within a single platform.

1. Status and Challenges of Previous System Operations

Three main systems were previously in operation for infectious disease information management and COVID-19 response. First, the IDMS centralized infectious disease management functions to overcome limitations experienced during the 2015 Middle East Respiratory Syndrome outbreak, such as poor situational awareness between central and local governments and challenges in transparent information disclosure. It managed infectious disease reporting and situational awareness (patient surveillance), testing and diagnosis (pathogen surveillance), case investigations of confirmed patients (epidemiological investigation), and national isolation bed capacity. Second, the QIS was established to computerize health declarations from international arrivals, reports of suspected cases, and quarantine results for vessels and aircrafts. It supported the full range of quarantine officer duties, including human quarantine, vessel and aircraft inspection, pre-departure vaccinations and certificate issuance, and disinfection record management. Finally, the CIMS was developed specifically for an effective COVID-19 response. Launched in December 2020, it retained the basic framework of the IDMS but included added functionalities exclusively for managing COVID-19-related tasks. Its main functions included screening center operations (e.g., electronic health questionnaires), polymerase chain reaction test cost settlements, self-administered epidemiological surveys, and the issuance of electronic certificates, such as the “vaccine pass,” by linking with vaccination data.

This siloed architecture hindered the systematic management of individual case histories: information from different stages was not integrated, and the lack of verification of the national identification number at the time of reporting led to difficulties in isolation and treatment management, reinfection and duplicate reporting, and an inability to check past infection records. Consequently, producing statistics and key indicators demanded excessive manpower and time, and the separate generation of statistics by various bodies—such as the Central Disease Control Headquarters, the Central Disaster and Safety Countermeasures Headquarters, and local governments—impeded timely data provision. Moreover, the legacy IDMS lacked uniformity and standardization in data entry. Adding new data fields without ensuring consistent data accumulation increased system complexity.

2. Core Values and Guiding Principles of the Integrated System

The Infectious Disease Information System was developed to address the limitations of previous systems, with three primary goals.

1) Operational efficiency

The system aimed to ensure data accuracy and integrity by linking the entire disease response process (quarantine, reporting, pathogen identification, and epidemiological investigation) based on unique personal identifiers and connecting with public information systems (e.g., Ministry of the Interior and Safety and National Health Insurance Service). It improved user convenience for data entry, minimized input errors, and established a new big data platform in a secure public cloud environment. It also sought to improve public convenience through collaboration with private platforms such as Kakao and Naver.

2) Information usability

The goal was to improve information quality by systematically standardizing data from the point of collection and to produce de-identified data as a source for research. By making these data accessible, the system aims to leverage private-sector expertise and establish an evidence-based foundation for infectious disease response.

3) Information integrity and validity of collection

Mutual integrity was confirmed by analyzing relevant laws, guidelines, and existing systems, while authorization and information access frameworks were refined. The validity of data collection was also ensured through measures such as mandatory prior notification for epidemiological investigations and clearly defined scopes for information linkage and access.

3. Detailed Implementation Strategy

1) Integration and linkage of information across the entire response process

By breaking down informational silos, the system integrated previously fragmented platforms by linking data across all stages of the infectious disease response, from quarantine to reporting, pathogen identification, epidemiological investigation, and patient management. Furthermore, it enhanced the accuracy and reliability of collected data by strengthening linkage and verification with external public information systems. Specifically, for Korean nationals, patient reports are verified in real time against the Resident Registration System of Korea, operated by the Ministry of the Interior and Safety, for name, national identification number, and address. For foreign nationals, name, nationality, date of birth, sex, and alien registration number are verified using the Ministry of Justice’s Personal information for foreigners. This process ensures data accuracy at the reporting stage through real-time verification and enables the automatic assignment of cases to the appropriate public health center based on address. Information on symptomatic individuals and confirmed patients identified in quarantine is now reported to the integrated system, making it accessible to officials in local governments and the KDCA. The system was redesigned to automatically link this information to subsequent tasks such as pathogen testing and epidemiological investigations. This has enabled the management of a comprehensive infectious disease history for each patient (Figure 1).

Figure 1. Status of the Infectious Disease Information System linkage
KDCA=Korea Disease Control and Prevention Agency; HIV=human immunodeficiency virus; AIDS=acquired immunodeficiency syndrome.

2) Standardization of epidemiological investigations

Data collection for epidemiological investigations of Class 1–3 comprehensive surveillance diseases was restructured into 11 modular categories, designed so that components within each category can be managed separately. Thus, modifying a common item requires updating only a single module for the change to be automatically reflected across all disease-specific forms, enabling rapid revisions revisions (Figure 2). Furthermore, data collection items were standardized: standard codes are used where available (e.g., Korean Standard Classification of Occupations, ISO 3166 for countries, KCD for underlying conditions), and for other items, uniform fields are used across all diseases. For instance, in previous investigation forms, “cefazolin” was recorded inconsistently with multiple spellings and abbreviations. This has now been standardized to “Cefazolin,” ensuring it is managed as a single data item. The structure was reformed to allow the public health center managing the patient—based on actual residence or presumed infection area, not just the registered address—to conduct investigations, depending on transmission dynamics or field conditions. For cluster cases spanning multiple regions, a coordinating public health center can be designated to enable information sharing and joint investigation.

Figure 2. Strategy for implementing modular epidemiological data collection
^a)Modularization of epidemiological survey data collection considering Level 2 (type of infectious disease)∙Level 3 (characteristics of individual infectious diseases).

3) Establishment of the Infectious Disease Big Data Platform

While the regular generation of disease-specific statistics is necessary, significant time was previously consumed by repetitive tasks such as data cleaning and merging. Therefore, the Infectious Disease Big Data Platform was established to support policy research and analysis by automatically generating user-required statistics from the integrated system’s data, supporting custom queries, and providing pseudonymized data to researchers on demand. The platform enables the extraction of routine statistics, such as periodic disease incidence reports, through a dedicated menu. It also supports customized analyses, including data visualization based on diverse indicators such as epidemiological analysis, pathogen test results, testing methods, and healthcare utilization patterns. The platform also provides a flexible analytical environment by allowing users to incorporate their own datasets for analysis alongside the system’s predefined data. These capabilities have enabled the use of collected data for direct policy support, as demonstrated by analyses of a pertussis outbreak [4] and the status of waterborne and foodborne disease outbreaks [5] by using information from the integrated system (Figure 3).

Figure 3. Infectious Disease Big Data Platform architecture
ODS=operational data store.

4) Enhanced response communication and infrastructure modernization

Public communication channels and certificate services were established, such as issuing certificates of hospitalization/isolation via the Government 24 portal and delivering hospitalization/isolation notices to mobile apps through the National Secretary Service. Furthermore, to ensure stable processing of large-scale data, the system was built on a cloud-based infrastructure within the National Information Resources Service of the Ministry of the Interior and Safety, securing operational flexibility for future pandemics.

The Infectious Disease Information System overcame the limitations of legacy systems by unifying previously fragmented platforms and creating a flexible, scalable architecture capable of handling large-scale outbreaks. It also resolved institutional issues by realigning functions inconsistent with laws and guidelines, establishing an individual-level information management framework, automating statistical production, centralizing data flow into the KDCA-led system, and standardizing data collection structures.

Although prompted by the COVID-19 crisis, the integrated system transcends its role as a short-term response tool, marking a paradigm shift in long-term infectious disease management. Its standardized data, real-time integration, and automated analysis and reporting systems are prime examples of the digital transformation of public health administration and are expected to directly influence the formulation of various public health policies.

The KDCA launched the Infectious Disease Information System and the Infectious Disease Big Data Platform in 2024 and is currently operating them stably. Furthermore, post-implementation research is underway to analyze the system’s impact on disease response efficiency and its socioeconomic effects, and to formulate future development strategies by studying similar systems that utilize the latest technologies. Continuous efforts are being made to improve the integrated system itself, in addition to enhancing user convenience. Beyond ensuring technical stability, the KDCA will continue to refine laws and institutions, solidify inter-agency cooperation, and cultivate professional talent for system operation and management.

Ethics Statement: Not applicable.

Funding Source: None.

Acknowledgments: None.

Conflict of Interest: Seongsun Kim is an editorial board member of the journal, but was not involved in the review process of this manuscript. Otherwise, there is no conflict of interest to declare.

Author Contributions: Conceptualization: SSK, JHP. Investigation: JHP, SYH. Project administration: JHP. Resources: JHP, SYH. Supervision: SSK. Writing–original draft: JHP. Writing–review & editing: JHP, SYH.