Evidence map›Paper›PMID 41210199›Full record

ArticleOne health (Amsterdam, Netherlands)2025

Challenges and recommendations for embracing digital tools for one health surveillance in LMICs: Viewpoints from a special session of 17th ISVEE.

Thang Nguyen-Tien, Fred Unger, Terdsak Yano, Florence Mutua, Elizabeth A J Cook, Hu Suk Lee, Bernard Bett, Hung Nguyen-Viet

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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

8 authors.

Thang Nguyen-TienInternational Livestock Research Institute, Hanoi, Viet Nam.
Fred UngerInternational Livestock Research Institute, Hanoi, Viet Nam.
Terdsak YanoChiang Mai University, Chiang Mai, Thailand.
Florence MutuaInternational Livestock Research Institute, Nairobi, Kenya.
Elizabeth A J CookInternational Livestock Research Institute, Nairobi, Kenya.
Hu Suk LeeCollege of Veterinary Medicine, Chungnam National University, Daejeon, Republic of Korea.
Bernard BettInternational Livestock Research Institute, Nairobi, Kenya.
Hung Nguyen-VietInternational Livestock Research Institute, Nairobi, Kenya.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The adoption of digital tools presents a critical opportunity to enhance One Health initiatives in low- and middle-income countries (LMICs). At the 17th International Symposium of Veterinary Epidemiology and Economics (ISVEE17), a special session explored the role of Information and Communication Technology (ICT) applications in addressing zoonoses, animal diseases, food safety, and antimicrobial resistance (AMR) in Asia and Africa countries. This paper highlights key insights from that session, indicating the barriers and opportunities for ICT implementation and expansion including user engagement and incentives, data quality and standardization, infrastructure, evidence and policy advocacy, capacity building, network and knowledge exchange, sustainability. The necessity of co-design, infrastructure investment, applications integration, interoperability and collaboration among international and national organizations, cross-sectoral and interdisciplinary approaches, continuous training and evidence-based policy support and sustainable funding models are crucial for building effective, inclusive, and scalable ICT-driven solutions.

Indexed as

Digital applicationsInformation communication technologyISVEE17LMICsOne health surveillance

Identifiers

PMID41210199
PMCPMC12590007

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.