Evidence map›Paper›PMID 42238664›Full record

ArticlePublic health weekly report2026

Characteristics of Animal Influenza Outbreaks and Human Infection Prevention Response Outcomes in the Honam Region, 2024-2025 Epidemic Season.

Seungjin Kim, Eun-Young Kim, HyeKyung In

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.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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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.

Seungjin KimDivision of infectious Disease Response, Honam Regional Center for Disease Control and Prevention, Korea Disease Control and Prevention Agency, Gwangju, Korea.ORCID https://orcid.org/0000-0001-7470-7293
Eun-Young KimDivision of infectious Disease Response, Honam Regional Center for Disease Control and Prevention, Korea Disease Control and Prevention Agency, Gwangju, Korea.ORCID https://orcid.org/0000-0002-7065-9746
HyeKyung InDivision of infectious Disease Response, Honam Regional Center for Disease Control and Prevention, Korea Disease Control and Prevention Agency, Gwangju, Korea.ORCID https://orcid.org/0000-0003-4485-6049

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: This report describes the epidemiological characteristics of animal influenza (AI) outbreaks and the features of high-risk human populations in the Honam region during the 2024-2025 epidemic season. It also aims to identify limitations observed in field responses and to propose areas for improvement to inform future strategies for the prevention and control of human AI infections. Methods: AI detection data from animal health authorities were examined according to pathogenicity, occurrence site, and administrative district, with monthly trends derived from specimen collection dates. High-risk individuals were identified using exposure investigation forms reported to national infectious disease information system, and were evaluated by occupation, age, and nationality. Suspected human cases were reviewed for clinical manifestations, epidemiologic links, and results of real-time reverse transcription polymerase chain reaction (RT-PCR) testing. Results: A total of 184 AI events were documented in the Honam region. Jeonbuk and Jeonnam primarily exhibited poultry farm-associated cases, whereas Gwangju predominantly showed cases associated with live bird markets. Initial detections occurred among wild birds, followed by a peak in poultry farm outbreaks in December. A total of 2,961 high-risk individuals were identified; over 80% were culling workers and 61.5% were foreign nationals. Four suspected human cases were recorded, all of which tested negative by RT-PCR. Conclusions: During the 2024-2025 epidemic season, AI outbreaks in the Honam region increased in scale compared with previous seasons, and occurrence patterns and the size of the high-risk population were closely associated with outbreak magnitude. Although no human AI infections were identified, the predominance of culling workers and the high proportion of foreign workers among high-risk groups, along with inadequate implementation of preventive measures, highlighted vulnerabilities in field-level response capacity. These findings call for strengthened information sharing between animal and human health authorities before the epidemic season, systematized culling procedures, enhanced multilingual education for foreign workers, and advanced stockpiling of preventive resources for high-risk populations.

Indexed as

Avian influenzaHigh-risk groupsHonam regionHuman infectionPublic health surveillance

Identifiers

PMID42238664
PMCPMC13228905

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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.