Evidence map›Paper›PMID 41334209›Full record

ArticleJugan geon-gang gwa jilbyeong2025

[Overview of Infectious Disease Information System and Big Data Platform].

Jonghyeon Park, Seonyeong Ha, Seongsun Kim

Abstract readEnglish Abstract
In one paragraph

Article in Jugan geon-gang gwa jilbyeong, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: To present the system capabilities of the restructured Infectious Disease Information System and Big Data Platform, aimed at improving the speed and efficiency of the response to infectious diseases. Methods: Following the coronavirus disease 2019 pandemic, the limitations of existing systems were analyzed. In response, the core values and strategic directions for the new system were established, along with detailed implementation plans. Results: The Infectious Disease Information System, built on unique identification data, enhanced data accuracy and usability by linking all phases of the infectious disease response to public information systems. Standardized reporting formats have unified analytical frameworks for various diseases. In addition, statistical production and customized analysis are supported through the Infectious Disease Big Data Platform and flexibility is secured by migrating to the National Information Resources Service to ensure stable processing of large-scale information. Conclusions: By standardizing and integrating disease surveillance and control data, the proposed system enables timely and accurate responses to infectious diseases. It is expected to function as essential infrastructure for future pandemic preparedness and enhanced infectious disease management.

Indexed as

Big Data PlatformInfectious Disease Information SystemIntegration and linkage of informationStandardization of epidemiological investigations

Identifiers

PMID41334209
PMCPMC12480214

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.