Evidence map›Paper›PMID 42473680›Full record

ArticlePublic health weekly report2026

Joint Publication of the First 2024-2025 National Influenza Annual Report by the Korea Disease Control and Prevention Agency and the National Health Insurance Service.

Boyeong Ryu, Jia Kim, Nam-Joo Lee, Minji Koo, Jeeyeon Shin, Eunjin Hyun, Gieun Choi, Yun Kyoung Kim, Jeongsuk Song, Dongkeun Kim and 7 more

Abstract read
In one paragraph

Article in Public health weekly report, 2026. 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

17 authors.

Boyeong Ryu *Division of Immunization Services, Department of Healthcare Safety and Immunization, Korea Disease Control and Prevention Agency, Cheongju, Korea.ORCID https://orcid.org/0000-0001-9336-8098
Jia Kim *Division of Infectious Disease Control, Department of Infectious Disease Policy, Korea Disease Control and Prevention Agency, Cheongju, Korea.ORCID https://orcid.org/0000-0003-2989-5533
Nam-Joo Lee *Division of Emerging Infectious Diseases, Department of Laboratory Diagnosis and analysis, Korea Disease Control and Prevention Agency, Cheongju, Korea.ORCID https://orcid.org/0000-0002-9488-9845
Minji Koo *Department of Artificial Intelligence, National Health Insurance Service, Wonju, Korea.ORCID https://orcid.org/0000-0001-5990-1354
Jeeyeon ShinDivision of Immunization Services, Department of Healthcare Safety and Immunization, Korea Disease Control and Prevention Agency, Cheongju, Korea.ORCID https://orcid.org/0000-0001-7960-1535
Eunjin HyunDivision of Immunization Services, Department of Healthcare Safety and Immunization, Korea Disease Control and Prevention Agency, Cheongju, Korea.ORCID https://orcid.org/0009-0007-8264-377X
Gieun ChoiDivision of Immunization Services, Department of Healthcare Safety and Immunization, Korea Disease Control and Prevention Agency, Cheongju, Korea.ORCID https://orcid.org/0009-0003-2373-4955
Yun Kyoung KimDivision of Infectious Disease Control, Department of Infectious Disease Policy, Korea Disease Control and Prevention Agency, Cheongju, Korea.ORCID https://orcid.org/0009-0005-3541-876X
Jeongsuk SongDivision of Infectious Disease Control, Department of Infectious Disease Policy, Korea Disease Control and Prevention Agency, Cheongju, Korea.ORCID https://orcid.org/0000-0002-4842-8140
Dongkeun KimDivision of Infectious Disease Control, Department of Infectious Disease Policy, Korea Disease Control and Prevention Agency, Cheongju, Korea.ORCID https://orcid.org/0000-0002-8589-4757
Hyungmin LeeDivision of Infectious Disease Control, Department of Infectious Disease Policy, Korea Disease Control and Prevention Agency, Cheongju, Korea.ORCID https://orcid.org/0000-0003-3478-3704
Eun-Jin KimDivision of Emerging Infectious Diseases, Department of Laboratory Diagnosis and analysis, Korea Disease Control and Prevention Agency, Cheongju, Korea.ORCID https://orcid.org/0000-0001-6784-8004
Hoyeon JangDepartment of Big Data Management, National Health Insurance Service, Wonju, Korea.ORCID https://orcid.org/0000-0002-5446-7752
Log Young KimDepartment of Big Data Management, National Health Insurance Service, Wonju, Korea.ORCID https://orcid.org/0000-0002-6160-8357
Somyung LeeDepartment of Big Data Management, National Health Insurance Service, Wonju, Korea.ORCID https://orcid.org/0009-0007-0684-5361
Jaiyong KimDepartment of Big Data Management, National Health Insurance Service, Wonju, Korea.ORCID https://orcid.org/0000-0003-0985-7871
Hyerim LeeDivision of Immunization Services, Department of Healthcare Safety and Immunization, Korea Disease Control and Prevention Agency, Cheongju, Korea.ORCID https://orcid.org/0000-0002-9495-2701

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: The first National Influenza Annual Report was jointly released by the Korea Disease Control and Prevention Agency (KDCA) and the National Health Insurance Service (NHIS) to provide a comprehensive analysis of influenza activity and the burden of disease during the 2024-2025 influenza season. Methods: Influenza activity was analyzed using patient- and pathogen-based surveillance data, medical costs data, vaccination coverage, and vaccine effectiveness (VE) estimates. Data were obtained from the KDCA sentinel surveillance system, the National Immunization Program, and the NHIS national health information databases. VE was estimated using both a target trial emulation (TTE)-based retrospective cohort design to assess age-specific outcomes and an interrupted time series (ITS) method with dynamic cohort to evaluate time-varying protection. Results: During the 2024-2025 season, influenza-like illness peaked at 99.8 cases per 1,000 outpatients in the first week of 2025, the highest level recorded since 2016. The overall influenza virus detection rate was 15.2%, with a winter wave dominated by influenza A and a spring wave of influenza B. NHIS claims identified approximately 3.86 million influenza cases, indicating a decline from the previous season. Despite this decrease in case numbers, total medical costs continued to increase in the post-coronavirus disease 2019 period, reaching 629.5 billion KRW, with hospitalization accounting for 77.3% of the total costs. Vaccination coverage was 70.0% among children aged 6 months to 13 years and 81.6% among adults aged 65 years and older. The TTE analysis showed that VE against severe outcomes ranged from 63.7% to 74.6%, whereas VE against mortality ranged from 52.2% to 81.1%, depending on the age group. The ITS method demonstrated that protection against hospitalization (VE 41.8%) persisted for up to 2 months after vaccination, whereas protection against mortality (VE 38.1%) persisted for up to 6 months. Overall, influenza vaccination was estimated to have prevented 143,868 influenza cases, including outpatient and inpatient cases, as well as 3,506 deaths. Conclusions: The findings presented in this annual report provide scientific evidence for optimizing national influenza prevention and response strategies and advancing immunization policy.

Indexed as

Annual reportBig dataInfluenzaPublic health surveillance

Identifiers

PMID42473680
PMCPMC13381087

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.