Evidence map›Paper›PMID 41049402›Full record

ArticleOne health (Amsterdam, Netherlands)2025

Integrating One Health governance in China: Assessing structural implementation and operational entry points.

Qi-Yu Zhang, Yan-Yan Zhang, Jing-Shu Liu, Xin-Chen Li, Ze-Lin Zhu, Xin-Yu Feng, Le-Fei Han, Chen-Di Zhu, Hein-Min Tun, Lian Zong and 1 more

Abstract read
In one paragraph

Article in One health (Amsterdam, Netherlands), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Global spread of carbapenem-resistantOne health (Amsterdam, Netherlands) · 2026
    Article
  3. Review
  4. Article
  5. Review
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  7. Review
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

11 authors.

Qi-Yu ZhangSchool of Global Health, Chinese Center for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China.
Yan-Yan ZhangSchool of Global Health, Chinese Center for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China.
Jing-Shu LiuNational Institute of Parasitic Diseases at Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research), NHC Key Laboratory of Parasite and Vector Biology, WHO Collaborating Centre for Tropical Diseases, Shanghai, People's Republic of China.
Xin-Chen LiSchool of Global Health, Chinese Center for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China.
Ze-Lin ZhuNational Institute of Parasitic Diseases at Chinese Center for Disease Control and Prevention (Chinese Center for Tropical Diseases Research), NHC Key Laboratory of Parasite and Vector Biology, WHO Collaborating Centre for Tropical Diseases, Shanghai, People's Republic of China.
Xin-Yu FengSchool of Global Health, Chinese Center for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China.
Le-Fei HanSchool of Global Health, Chinese Center for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China.
Chen-Di ZhuJockey Club School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, SAR 999077, China.
Hein-Min TunJockey Club School of Public Health and Primary Care, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, SAR 999077, China.
Lian ZongShanghai Baoshan District Center for Disease Control and Prevention (Shanghai Baoshan District Health Inspection and Supervision Institute), Shanghai, People's Republic of China.
Xiaoxi ZhangSchool of Global Health, Chinese Center for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: In China, despite the establishment of a top-level One Health framework to address the interconnected risks of zoonotic diseases, antimicrobial resistance (AMR), and environmental degradation, significant challenges persist in translating this vision into effective implementation. The country's large agricultural sector, dense population, and diverse ecosystems require coordinated governance across human, animal, and environmental health sectors. However, gaps remain in resource allocation, cross-sector coordination, and policy integration. This study evaluates China's One Health governance through four structural domains-Monitoring & Evaluation, Intervention & Response, Surveillance & Early Warning, and Capacity Building-and four operational entry points-Technology, Information, Human Resources, and Finance. The aim is to identify strengths, gaps, and provide actionable recommendations for improvement. Methods: A qualitative approach was employed, involving 41 in-depth expert interviews, policy document analysis, and a systematic literature review. Interviews were conducted with stakeholders from public health, veterinary services, and environmental agencies, focusing on key domains of the One Health implementation. Data were thematically coded using NVivo 12.0 and analyzed using Grounded Theory. The results were cross-checked through intercoder reliability testing to provide actionable recommendations. Results: While regular reporting mechanisms exist for Monitoring & Evaluation across human, animal, and environmental health sectors, real-time assessments remain insufficient, limiting timely, multisectoral responses to emerging health risks. A tiered emergency system supports Intervention & Response, but inefficiencies in cross-sector resource allocation and coordination hinder its effectiveness. In Surveillance & Early Warning, fragmented data collection and interdepartmental silos across different health domains impede comprehensive and integrated risk monitoring. Despite existing Capacity Building programs, large-scale interdisciplinary exercises and continuous skill development opportunities remain scarce. Operationally, diagnostic technologies like polymerase chain reaction (PCR) and geographic information system (GIS) are available but unevenly distributed. Data-sharing mechanisms exist, but bureaucratic delays and inconsistent standards hinder integration. Workforce gaps, an aging cohort, and insufficient multidisciplinary training threaten the sustainability of the One Health framework. Operational budgets and personnel incentives remain inadequate, limiting the impact of financial investments. Conclusion: Despite progress in policy and infrastructure, China faces critical gaps in One Health implementation, particularly in real-time monitoring, cross-sectoral coordination, data integration, workforce capacity, and financial support. Addressing these gaps is crucial for enhancing One Health governance and offers valuable lessons for other regions with similar challenges in integrating human, animal, and environmental health.

Indexed as

One Health entry pointsOne Health governanceOne Health implementation

Identifiers

PMID41049402
PMCPMC12495039

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.