Evidence map›Paper›PMID 40168512›Full record

ReviewJournal of global health2025

Enhancing human and animal health data integration and informed actions for pandemic preparedness at the primary healthcare level: a multisectoral conceptual framework.

Bach Xuan Tran, Ha Ngoc Vu, David B Duong, Laurent Boyer, Tran Hoang Long, Duy Cao Nguyen, Shenglan Tang

Abstract readReview
In one paragraph

Review in Journal of global health, 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

7 authors.

Bach Xuan TranFaculty of Public Health, VNU University of Medicine and Pharmacy, Vietnam National University, Hanoi, Vietnam.
Ha Ngoc VuFaculty of Public Health, VNU University of Medicine and Pharmacy, Vietnam National University, Hanoi, Vietnam.
David B DuongDivision of Global Health Equity, Brigham and Women's Hospital, Boston, Massachusetts, USA.
Laurent BoyerCEReSS-Health Services Research and Quality of Life Center, Aix-Marseille University, France.
Tran Hoang LongAston University, Birmingham, UK.
Duy Cao NguyenVNU University of Economics and Business, Vietnam National University, Hanoi, Vietnam.
Shenglan TangInstitute for Global Health Innovations, Duy Tan University, Vietnam.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A key priority for strengthening global health capacity for pandemic response is rapid risk assessment for timely, context-specific decision-making. However, integrating human and animal health data for preparedness remains a challenge, especially at the primary healthcare (PHC) level. Here we review Vietnam's pandemic response and propose a conceptual framework for improving data integration across sectors in low- and middle-income countries. Despite the country's progress in health information systems and telehealth, disparities in data use and coordination between human and animal health sectors hindered effective responses. Existing mechanisms between healthcare and veterinary professionals lack integrated data-sharing, delaying risk communication and crisis management, particularly in rural areas with limited IT access and infrastructure. The proposed model includes five components: data interoperability with standardised indicators for real-time synthesis; robust digital health infrastructure and telehealth expansion; capacity building in data management for health and veterinary professionals; epidemic intelligence tools for risk assessment; and evidence-driven decision-making for coordinated epidemic responses. This model offers a pathway to strengthen health systems and improve pandemic preparedness at the PHC level in Vietnam and similar settings.

Indexed as

Pandemic PreparednessPandemicsPrimary Health CareAnimalsCapacity BuildingHumansRisk AssessmentTelemedicineVietnam

Identifiers

PMID40168512
PMCPMC11961054

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.